{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import os\n",
    "os.environ['CUDA_VISIBLE_DEVICES'] = '1'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/husein/.local/lib/python3.6/site-packages/tensorflow/python/framework/dtypes.py:516: FutureWarning: Passing (type, 1) or '1type' as a synonym of type is deprecated; in a future version of numpy, it will be understood as (type, (1,)) / '(1,)type'.\n",
      "  _np_qint8 = np.dtype([(\"qint8\", np.int8, 1)])\n",
      "/home/husein/.local/lib/python3.6/site-packages/tensorflow/python/framework/dtypes.py:517: FutureWarning: Passing (type, 1) or '1type' as a synonym of type is deprecated; in a future version of numpy, it will be understood as (type, (1,)) / '(1,)type'.\n",
      "  _np_quint8 = np.dtype([(\"quint8\", np.uint8, 1)])\n",
      "/home/husein/.local/lib/python3.6/site-packages/tensorflow/python/framework/dtypes.py:518: FutureWarning: Passing (type, 1) or '1type' as a synonym of type is deprecated; in a future version of numpy, it will be understood as (type, (1,)) / '(1,)type'.\n",
      "  _np_qint16 = np.dtype([(\"qint16\", np.int16, 1)])\n",
      "/home/husein/.local/lib/python3.6/site-packages/tensorflow/python/framework/dtypes.py:519: FutureWarning: Passing (type, 1) or '1type' as a synonym of type is deprecated; in a future version of numpy, it will be understood as (type, (1,)) / '(1,)type'.\n",
      "  _np_quint16 = np.dtype([(\"quint16\", np.uint16, 1)])\n",
      "/home/husein/.local/lib/python3.6/site-packages/tensorflow/python/framework/dtypes.py:520: FutureWarning: Passing (type, 1) or '1type' as a synonym of type is deprecated; in a future version of numpy, it will be understood as (type, (1,)) / '(1,)type'.\n",
      "  _np_qint32 = np.dtype([(\"qint32\", np.int32, 1)])\n",
      "/home/husein/.local/lib/python3.6/site-packages/tensorflow/python/framework/dtypes.py:525: FutureWarning: Passing (type, 1) or '1type' as a synonym of type is deprecated; in a future version of numpy, it will be understood as (type, (1,)) / '(1,)type'.\n",
      "  np_resource = np.dtype([(\"resource\", np.ubyte, 1)])\n",
      "/home/husein/.local/lib/python3.6/site-packages/tensorboard/compat/tensorflow_stub/dtypes.py:541: FutureWarning: Passing (type, 1) or '1type' as a synonym of type is deprecated; in a future version of numpy, it will be understood as (type, (1,)) / '(1,)type'.\n",
      "  _np_qint8 = np.dtype([(\"qint8\", np.int8, 1)])\n",
      "/home/husein/.local/lib/python3.6/site-packages/tensorboard/compat/tensorflow_stub/dtypes.py:542: FutureWarning: Passing (type, 1) or '1type' as a synonym of type is deprecated; in a future version of numpy, it will be understood as (type, (1,)) / '(1,)type'.\n",
      "  _np_quint8 = np.dtype([(\"quint8\", np.uint8, 1)])\n",
      "/home/husein/.local/lib/python3.6/site-packages/tensorboard/compat/tensorflow_stub/dtypes.py:543: FutureWarning: Passing (type, 1) or '1type' as a synonym of type is deprecated; in a future version of numpy, it will be understood as (type, (1,)) / '(1,)type'.\n",
      "  _np_qint16 = np.dtype([(\"qint16\", np.int16, 1)])\n",
      "/home/husein/.local/lib/python3.6/site-packages/tensorboard/compat/tensorflow_stub/dtypes.py:544: FutureWarning: Passing (type, 1) or '1type' as a synonym of type is deprecated; in a future version of numpy, it will be understood as (type, (1,)) / '(1,)type'.\n",
      "  _np_quint16 = np.dtype([(\"quint16\", np.uint16, 1)])\n",
      "/home/husein/.local/lib/python3.6/site-packages/tensorboard/compat/tensorflow_stub/dtypes.py:545: FutureWarning: Passing (type, 1) or '1type' as a synonym of type is deprecated; in a future version of numpy, it will be understood as (type, (1,)) / '(1,)type'.\n",
      "  _np_qint32 = np.dtype([(\"qint32\", np.int32, 1)])\n",
      "/home/husein/.local/lib/python3.6/site-packages/tensorboard/compat/tensorflow_stub/dtypes.py:550: FutureWarning: Passing (type, 1) or '1type' as a synonym of type is deprecated; in a future version of numpy, it will be understood as (type, (1,)) / '(1,)type'.\n",
      "  np_resource = np.dtype([(\"resource\", np.ubyte, 1)])\n"
     ]
    }
   ],
   "source": [
    "import librosa\n",
    "import tensorflow as tf\n",
    "import glob\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pickle\n",
    "\n",
    "with open('train-wav.pkl', 'rb') as fopen:\n",
    "    X = pickle.load(fopen)['X']\n",
    "    \n",
    "with open('test-wav.pkl', 'rb') as fopen:\n",
    "    Y = pickle.load(fopen)['Y']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "# follow hyperparameters from here, https://github.com/pytorch/fairseq/tree/master/examples/wav2vec\n",
    "\n",
    "features = [(512, 10, 5), (512, 8, 4), (512, 4, 2), (512, 4, 2), (512, 4, 2), (512, 1, 1), (512, 1, 1)]\n",
    "aggs = [(512, 2, 1), (512, 3, 1), (512, 4, 1), (512, 5, 1), (512, 6, 1), (512, 7, 1), (512, 8, 1), (512, 9, 1), \n",
    "        (512, 10, 1), (512, 11, 1), (512, 12, 1), (512, 13, 1)]\n",
    "num_negatives = 10\n",
    "prediction_steps = 12\n",
    "learning_rate = 1e-5\n",
    "min_learning_rate = 1e-9\n",
    "max_learning_rate = 0.005\n",
    "learning_scheduler = 'cosine'\n",
    "max_update = 400000\n",
    "residual_scale = 0.5\n",
    "log_compression = True\n",
    "warmup_updates = 50\n",
    "warmup_init_lr = 1e-7\n",
    "batch_size = 24\n",
    "epoch = 10\n",
    "total_steps = batch_size * epoch"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "# tf.compat.v1.enable_eager_execution()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "import math\n",
    "import re\n",
    "\n",
    "def create_optimizer(loss, init_lr, num_train_steps, num_warmup_steps):\n",
    "    \"\"\"Creates an optimizer training op.\"\"\"\n",
    "    global_step = tf.train.get_or_create_global_step()\n",
    "    learning_rate = tf.constant(value = init_lr, shape = [], dtype = tf.float32)\n",
    "    learning_rate = tf.train.polynomial_decay(\n",
    "        learning_rate,\n",
    "        global_step,\n",
    "        num_train_steps,\n",
    "        end_learning_rate = 0.0,\n",
    "        power = 1.0,\n",
    "        cycle = False,\n",
    "    )\n",
    "\n",
    "    if num_warmup_steps:\n",
    "        global_steps_int = tf.cast(global_step, tf.int32)\n",
    "        warmup_steps_int = tf.constant(num_warmup_steps, dtype = tf.int32)\n",
    "\n",
    "        global_steps_float = tf.cast(global_steps_int, tf.float32)\n",
    "        warmup_steps_float = tf.cast(warmup_steps_int, tf.float32)\n",
    "\n",
    "        warmup_percent_done = global_steps_float / warmup_steps_float\n",
    "        warmup_learning_rate = init_lr * warmup_percent_done\n",
    "\n",
    "        is_warmup = tf.cast(global_steps_int < warmup_steps_int, tf.float32)\n",
    "        learning_rate = (\n",
    "            1.0 - is_warmup\n",
    "        ) * learning_rate + is_warmup * warmup_learning_rate\n",
    "    \n",
    "#     optimizer = tf.train.RMSPropOptimizer(learning_rate)\n",
    "#     optimizer = tf.train.AdamOptimizer(learning_rate)\n",
    "\n",
    "    optimizer = AdamWeightDecayOptimizer(\n",
    "        learning_rate = learning_rate,\n",
    "        weight_decay_rate = 0.01,\n",
    "        beta_1 = 0.9,\n",
    "        beta_2 = 0.999,\n",
    "        epsilon = 1e-6,\n",
    "        exclude_from_weight_decay = ['LayerNorm', 'layer_norm', 'bias'],\n",
    "    )\n",
    "\n",
    "    tvars = tf.trainable_variables()\n",
    "    grads = tf.gradients(loss, tvars)\n",
    "\n",
    "    # This is how the model was pre-trained.\n",
    "    # (grads, _) = tf.clip_by_global_norm(grads, clip_norm = 1.0)\n",
    "\n",
    "    train_op = optimizer.apply_gradients(\n",
    "        zip(grads, tvars), global_step = global_step\n",
    "    )\n",
    "\n",
    "    new_global_step = global_step + 1\n",
    "    train_op = tf.group(train_op, [global_step.assign(new_global_step)])\n",
    "    return train_op\n",
    "\n",
    "\n",
    "class AdamWeightDecayOptimizer(tf.train.Optimizer):\n",
    "    \"\"\"A basic Adam optimizer that includes \"correct\" L2 weight decay.\"\"\"\n",
    "\n",
    "    def __init__(\n",
    "        self,\n",
    "        learning_rate,\n",
    "        weight_decay_rate = 0.0,\n",
    "        beta_1 = 0.9,\n",
    "        beta_2 = 0.999,\n",
    "        epsilon = 1e-6,\n",
    "        exclude_from_weight_decay = None,\n",
    "        name = 'AdamWeightDecayOptimizer',\n",
    "    ):\n",
    "        \"\"\"Constructs a AdamWeightDecayOptimizer.\"\"\"\n",
    "        super(AdamWeightDecayOptimizer, self).__init__(False, name)\n",
    "\n",
    "        self.learning_rate = learning_rate\n",
    "        self.weight_decay_rate = weight_decay_rate\n",
    "        self.beta_1 = beta_1\n",
    "        self.beta_2 = beta_2\n",
    "        self.epsilon = epsilon\n",
    "        self.exclude_from_weight_decay = exclude_from_weight_decay\n",
    "\n",
    "    def apply_gradients(self, grads_and_vars, global_step = None, name = None):\n",
    "        \"\"\"See base class.\"\"\"\n",
    "        assignments = []\n",
    "        for (grad, param) in grads_and_vars:\n",
    "            if grad is None or param is None:\n",
    "                continue\n",
    "\n",
    "            param_name = self._get_variable_name(param.name)\n",
    "\n",
    "            m = tf.get_variable(\n",
    "                name = param_name + '/adam_m',\n",
    "                shape = param.shape.as_list(),\n",
    "                dtype = tf.float32,\n",
    "                trainable = False,\n",
    "                initializer = tf.zeros_initializer(),\n",
    "            )\n",
    "            v = tf.get_variable(\n",
    "                name = param_name + '/adam_v',\n",
    "                shape = param.shape.as_list(),\n",
    "                dtype = tf.float32,\n",
    "                trainable = False,\n",
    "                initializer = tf.zeros_initializer(),\n",
    "            )\n",
    "            next_m = tf.multiply(self.beta_1, m) + tf.multiply(\n",
    "                1.0 - self.beta_1, grad\n",
    "            )\n",
    "            next_v = tf.multiply(self.beta_2, v) + tf.multiply(\n",
    "                1.0 - self.beta_2, tf.square(grad)\n",
    "            )\n",
    "\n",
    "            update = next_m / (tf.sqrt(next_v) + self.epsilon)\n",
    "            if self._do_use_weight_decay(param_name):\n",
    "                update += self.weight_decay_rate * param\n",
    "\n",
    "            update_with_lr = self.learning_rate * update\n",
    "\n",
    "            next_param = param - update_with_lr\n",
    "\n",
    "            assignments.extend(\n",
    "                [param.assign(next_param), m.assign(next_m), v.assign(next_v)]\n",
    "            )\n",
    "        return tf.group(*assignments, name = name)\n",
    "\n",
    "    def _do_use_weight_decay(self, param_name):\n",
    "        \"\"\"Whether to use L2 weight decay for `param_name`.\"\"\"\n",
    "        if not self.weight_decay_rate:\n",
    "            return False\n",
    "        if self.exclude_from_weight_decay:\n",
    "            for r in self.exclude_from_weight_decay:\n",
    "                if re.search(r, param_name) is not None:\n",
    "                    return False\n",
    "        return True\n",
    "\n",
    "    def _get_variable_name(self, param_name):\n",
    "        \"\"\"Get the variable name from the tensor name.\"\"\"\n",
    "        m = re.match('^(.*):\\\\d+$', param_name)\n",
    "        if m is not None:\n",
    "            param_name = m.group(1)\n",
    "        return param_name\n",
    "\n",
    "def gelu(x):\n",
    "    cdf = 0.5 * (1.0 + tf.tanh(\n",
    "      (np.sqrt(2 / np.pi) * (x + 0.044715 * tf.pow(x, 3)))))\n",
    "    return x * cdf\n",
    "\n",
    "def layer_norm(input_tensor, name=None):\n",
    "    return tf.contrib.layers.layer_norm(\n",
    "      inputs=input_tensor, begin_norm_axis=1, begin_params_axis=-1, scope=name)\n",
    "\n",
    "\n",
    "def cnn_block(x, hidden_dim, kernel_size, strides):\n",
    "    x =  tf.layers.conv1d(inputs = x,\n",
    "                          filters = hidden_dim,\n",
    "                          kernel_size = kernel_size,\n",
    "                          strides = strides)\n",
    "    \n",
    "    x = layer_norm(x)\n",
    "    # x = gelu(x)\n",
    "    x = tf.nn.relu6(x)\n",
    "    return x\n",
    "\n",
    "def cnn_aggregator(x, hidden_dim, kernel_size, strides):\n",
    "    ka = kernel_size // 2\n",
    "    kb = ka - 1 if kernel_size % 2 == 0 else ka\n",
    "    pad = tf.zeros([tf.shape(x)[0], kb + ka, hidden_dim])\n",
    "    x =  tf.layers.conv1d(inputs = tf.concat([pad, x], 1),\n",
    "                          filters = hidden_dim,\n",
    "                          kernel_size = kernel_size,\n",
    "                          strides = strides)\n",
    "    \n",
    "    x = layer_norm(x)\n",
    "    # x = gelu(x)\n",
    "    x = tf.nn.relu6(x)\n",
    "    return x\n",
    "\n",
    "def negative_sample(y):\n",
    "    bsz = tf.shape(y)[0]\n",
    "    fsz = tf.shape(y)[1]\n",
    "    tsz = tf.shape(y)[2]\n",
    "    \n",
    "    # b, d, t -> d, b, t\n",
    "    y = tf.transpose(y, [1, 0, 2])\n",
    "    y = tf.reshape(y, (fsz, -1))\n",
    "    neg_idxs = tf.random_uniform((bsz, num_negatives * tsz), minval=0, maxval=tsz, dtype=tf.int32)\n",
    "    \n",
    "    ranged = tf.expand_dims(tf.range(1, bsz), axis = 1)\n",
    "    a = tf.add(neg_idxs[1:bsz], tf.tile(ranged, [1, num_negatives * tsz]) * tsz)\n",
    "    \n",
    "    neg_idxs = tf.concat([neg_idxs[:1], a, neg_idxs[bsz:]], axis = 0)\n",
    "    neg_idxs = tf.reshape(neg_idxs, [-1])\n",
    "    negs = tf.gather(y, neg_idxs, axis=1)\n",
    "    negs = tf.reshape(negs, (fsz, bsz, num_negatives, tsz))\n",
    "    negs = tf.transpose(negs, [2, 1, 0, 3])\n",
    "    return negs\n",
    "\n",
    "class Model:\n",
    "    def __init__(self):\n",
    "        self.X = tf.placeholder(tf.float32, (None, None))\n",
    "        feature = tf.expand_dims(self.X, axis = 2)\n",
    "        \n",
    "        for no, f in enumerate(features):\n",
    "            size_layers = f[0]\n",
    "            kernel_size = f[1]\n",
    "            strides = f[2]\n",
    "            with tf.variable_scope('feature_%d'%no):\n",
    "                feature = cnn_block(feature, size_layers, kernel_size, strides)\n",
    "        \n",
    "        if log_compression:\n",
    "            feature = tf.math.abs(feature)\n",
    "            feature = feature + 1\n",
    "            feature = tf.math.log(feature)\n",
    "        \n",
    "        x = tf.identity(feature)\n",
    "        self.targets = tf.identity(feature)\n",
    "        for no, f in enumerate(aggs):\n",
    "            size_layers = f[0]\n",
    "            kernel_size = f[1]\n",
    "            strides = f[2]\n",
    "            with tf.variable_scope('agg_%d'%no):\n",
    "                x = cnn_aggregator(x, size_layers, kernel_size, strides)\n",
    "                \n",
    "        jin = 0\n",
    "        rin = 0\n",
    "        for _, k, stride in features:\n",
    "            if rin == 0:\n",
    "                rin = k\n",
    "            rin = rin + (k - 1) * jin\n",
    "            if jin == 0:\n",
    "                jin = stride\n",
    "            else:\n",
    "                jin *= stride\n",
    "        offset = math.ceil(rin / jin)\n",
    "\n",
    "        offset = int(offset)\n",
    "        \n",
    "        self.logits = x\n",
    "        transpose_targets = tf.transpose(self.targets, (0, 2, 1))\n",
    "        self.negatives = negative_sample(transpose_targets)\n",
    "        \n",
    "        y = tf.expand_dims(transpose_targets, axis = 0)\n",
    "        targets = tf.concat([y, self.negatives], axis = 0)\n",
    "        b = tf.shape(targets)[0]\n",
    "\n",
    "        x = tf.expand_dims(tf.transpose(self.logits, (0, 2, 1)), axis = -1)\n",
    "        x = tf.layers.conv2d_transpose(x, prediction_steps, (1, 1))\n",
    "        x = tf.expand_dims(x, axis = 0) \n",
    "        x = tf.tile(x, [b, 1, 1, 1, 1])\n",
    "        \n",
    "        copies = tf.shape(x)[0]\n",
    "        bsz = tf.shape(x)[1]\n",
    "        dim = tf.shape(x)[2]\n",
    "        tsz = tf.shape(x)[3]\n",
    "        steps = tf.shape(x)[4]\n",
    "        \n",
    "        steps = tf.math.minimum(steps, tsz - offset)\n",
    "        predictions = tf.zeros(bsz * copies * (tsz - offset + 1) * \\\n",
    "                               steps - ((steps + 1) * steps // 2) * copies * bsz)\n",
    "        labels = tf.zeros_like(predictions)\n",
    "        \n",
    "        def body(i, start, end, predictions, labels, offset):\n",
    "            offset = i + offset\n",
    "            end = start + (tsz - offset) * bsz * copies\n",
    "            pos_num = (end - start) // copies\n",
    "            s = tf.reduce_sum((x[:, :, :, :-offset, i] * targets[:, :, :, offset:]), axis = 2)\n",
    "            s = tf.reshape(s, [-1])\n",
    "            s = tf.pad(s, [[start, tf.shape(predictions)[0] - (start + tf.shape(s)[0])]])\n",
    "            predictions = tf.add(predictions, s)\n",
    "            pos_num = tf.cond(pos_num > 0, lambda: pos_num, lambda: 0)\n",
    "            l = tf.ones((pos_num))\n",
    "            l = tf.pad(l, [[start, tf.shape(labels)[0] - (start + pos_num)]])\n",
    "            labels = tf.add(labels, l)\n",
    "            return i + 1, end, end, predictions, labels, offset\n",
    "\n",
    "        def condition(i, start, end, predictions, labels, offset):\n",
    "            return i < steps\n",
    "\n",
    "        ranged = tf.Variable(tf.constant(0))\n",
    "        _, _, _, predictions, labels, _ = tf.while_loop(condition, body, [0, 0, 0, predictions, labels, offset])\n",
    "        self.predictions = predictions\n",
    "        self.labels = labels\n",
    "        \n",
    "        label_weights = tf.abs(tf.sign(self.predictions))\n",
    "        \n",
    "        numerator = tf.nn.sigmoid_cross_entropy_with_logits(\n",
    "            labels=self.labels,\n",
    "            logits=self.predictions) * label_weights\n",
    "        numerator = tf.reduce_sum(numerator)\n",
    "        denominator = tf.reduce_sum(label_weights) + 1e-5\n",
    "        self.cost = numerator / denominator\n",
    "        print(self.cost)\n",
    "        self.optimizer = create_optimizer(self.cost, learning_rate, total_steps, warmup_updates)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "WARNING:tensorflow:Entity <bound method Conv1D.call of <tensorflow.python.layers.convolutional.Conv1D object at 0x7f138815aa20>> could not be transformed and will be executed as-is. Please report this to the AutgoGraph team. When filing the bug, set the verbosity to 10 (on Linux, `export AUTOGRAPH_VERBOSITY=10`) and attach the full output. Cause: converting <bound method Conv1D.call of <tensorflow.python.layers.convolutional.Conv1D object at 0x7f138815aa20>>: AssertionError: Bad argument number for Name: 3, expecting 4\n",
      "WARNING: Entity <bound method Conv1D.call of <tensorflow.python.layers.convolutional.Conv1D object at 0x7f138815aa20>> could not be transformed and will be executed as-is. Please report this to the AutgoGraph team. When filing the bug, set the verbosity to 10 (on Linux, `export AUTOGRAPH_VERBOSITY=10`) and attach the full output. Cause: converting <bound method Conv1D.call of <tensorflow.python.layers.convolutional.Conv1D object at 0x7f138815aa20>>: AssertionError: Bad argument number for Name: 3, expecting 4\n",
      "WARNING:tensorflow:Entity <bound method Conv1D.call of <tensorflow.python.layers.convolutional.Conv1D object at 0x7f138815ae10>> could not be transformed and will be executed as-is. Please report this to the AutgoGraph team. When filing the bug, set the verbosity to 10 (on Linux, `export AUTOGRAPH_VERBOSITY=10`) and attach the full output. Cause: converting <bound method Conv1D.call of <tensorflow.python.layers.convolutional.Conv1D object at 0x7f138815ae10>>: AssertionError: Bad argument number for Name: 3, expecting 4\n",
      "WARNING: Entity <bound method Conv1D.call of <tensorflow.python.layers.convolutional.Conv1D object at 0x7f138815ae10>> could not be transformed and will be executed as-is. Please report this to the AutgoGraph team. When filing the bug, set the verbosity to 10 (on Linux, `export AUTOGRAPH_VERBOSITY=10`) and attach the full output. Cause: converting <bound method Conv1D.call of <tensorflow.python.layers.convolutional.Conv1D object at 0x7f138815ae10>>: AssertionError: Bad argument number for Name: 3, expecting 4\n",
      "WARNING:tensorflow:Entity <bound method Conv1D.call of <tensorflow.python.layers.convolutional.Conv1D object at 0x7f138815add8>> could not be transformed and will be executed as-is. Please report this to the AutgoGraph team. When filing the bug, set the verbosity to 10 (on Linux, `export AUTOGRAPH_VERBOSITY=10`) and attach the full output. Cause: converting <bound method Conv1D.call of <tensorflow.python.layers.convolutional.Conv1D object at 0x7f138815add8>>: AssertionError: Bad argument number for Name: 3, expecting 4\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/husein/.local/lib/python3.6/site-packages/tensorflow/python/client/session.py:1735: UserWarning: An interactive session is already active. This can cause out-of-memory errors in some cases. You must explicitly call `InteractiveSession.close()` to release resources held by the other session(s).\n",
      "  warnings.warn('An interactive session is already active. This can '\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "WARNING: Entity <bound method Conv1D.call of <tensorflow.python.layers.convolutional.Conv1D object at 0x7f138815add8>> could not be transformed and will be executed as-is. Please report this to the AutgoGraph team. When filing the bug, set the verbosity to 10 (on Linux, `export AUTOGRAPH_VERBOSITY=10`) and attach the full output. Cause: converting <bound method Conv1D.call of <tensorflow.python.layers.convolutional.Conv1D object at 0x7f138815add8>>: AssertionError: Bad argument number for Name: 3, expecting 4\n",
      "WARNING:tensorflow:Entity <bound method Conv1D.call of <tensorflow.python.layers.convolutional.Conv1D object at 0x7f138815ab70>> could not be transformed and will be executed as-is. Please report this to the AutgoGraph team. When filing the bug, set the verbosity to 10 (on Linux, `export AUTOGRAPH_VERBOSITY=10`) and attach the full output. Cause: converting <bound method Conv1D.call of <tensorflow.python.layers.convolutional.Conv1D object at 0x7f138815ab70>>: AssertionError: Bad argument number for Name: 3, expecting 4\n",
      "WARNING: Entity <bound method Conv1D.call of <tensorflow.python.layers.convolutional.Conv1D object at 0x7f138815ab70>> could not be transformed and will be executed as-is. Please report this to the AutgoGraph team. When filing the bug, set the verbosity to 10 (on Linux, `export AUTOGRAPH_VERBOSITY=10`) and attach the full output. Cause: converting <bound method Conv1D.call of <tensorflow.python.layers.convolutional.Conv1D object at 0x7f138815ab70>>: AssertionError: Bad argument number for Name: 3, expecting 4\n",
      "WARNING:tensorflow:Entity <bound method Conv1D.call of <tensorflow.python.layers.convolutional.Conv1D object at 0x7f138815ab00>> could not be transformed and will be executed as-is. Please report this to the AutgoGraph team. When filing the bug, set the verbosity to 10 (on Linux, `export AUTOGRAPH_VERBOSITY=10`) and attach the full output. Cause: converting <bound method Conv1D.call of <tensorflow.python.layers.convolutional.Conv1D object at 0x7f138815ab00>>: AssertionError: Bad argument number for Name: 3, expecting 4\n",
      "WARNING: Entity <bound method Conv1D.call of <tensorflow.python.layers.convolutional.Conv1D object at 0x7f138815ab00>> could not be transformed and will be executed as-is. Please report this to the AutgoGraph team. When filing the bug, set the verbosity to 10 (on Linux, `export AUTOGRAPH_VERBOSITY=10`) and attach the full output. Cause: converting <bound method Conv1D.call of <tensorflow.python.layers.convolutional.Conv1D object at 0x7f138815ab00>>: AssertionError: Bad argument number for Name: 3, expecting 4\n",
      "WARNING:tensorflow:Entity <bound method Conv1D.call of <tensorflow.python.layers.convolutional.Conv1D object at 0x7f138808e400>> could not be transformed and will be executed as-is. Please report this to the AutgoGraph team. When filing the bug, set the verbosity to 10 (on Linux, `export AUTOGRAPH_VERBOSITY=10`) and attach the full output. Cause: converting <bound method Conv1D.call of <tensorflow.python.layers.convolutional.Conv1D object at 0x7f138808e400>>: AssertionError: Bad argument number for Name: 3, expecting 4\n",
      "WARNING: Entity <bound method Conv1D.call of <tensorflow.python.layers.convolutional.Conv1D object at 0x7f138808e400>> could not be transformed and will be executed as-is. Please report this to the AutgoGraph team. When filing the bug, set the verbosity to 10 (on Linux, `export AUTOGRAPH_VERBOSITY=10`) and attach the full output. Cause: converting <bound method Conv1D.call of <tensorflow.python.layers.convolutional.Conv1D object at 0x7f138808e400>>: AssertionError: Bad argument number for Name: 3, expecting 4\n",
      "WARNING:tensorflow:Entity <bound method Conv1D.call of <tensorflow.python.layers.convolutional.Conv1D object at 0x7f138815ae48>> could not be transformed and will be executed as-is. Please report this to the AutgoGraph team. When filing the bug, set the verbosity to 10 (on Linux, `export AUTOGRAPH_VERBOSITY=10`) and attach the full output. Cause: converting <bound method Conv1D.call of <tensorflow.python.layers.convolutional.Conv1D object at 0x7f138815ae48>>: AssertionError: Bad argument number for Name: 3, expecting 4\n",
      "WARNING: Entity <bound method Conv1D.call of <tensorflow.python.layers.convolutional.Conv1D object at 0x7f138815ae48>> could not be transformed and will be executed as-is. Please report this to the AutgoGraph team. When filing the bug, set the verbosity to 10 (on Linux, `export AUTOGRAPH_VERBOSITY=10`) and attach the full output. Cause: converting <bound method Conv1D.call of <tensorflow.python.layers.convolutional.Conv1D object at 0x7f138815ae48>>: AssertionError: Bad argument number for Name: 3, expecting 4\n",
      "WARNING:tensorflow:Entity <bound method Conv1D.call of <tensorflow.python.layers.convolutional.Conv1D object at 0x7f13701ab2b0>> could not be transformed and will be executed as-is. Please report this to the AutgoGraph team. When filing the bug, set the verbosity to 10 (on Linux, `export AUTOGRAPH_VERBOSITY=10`) and attach the full output. Cause: converting <bound method Conv1D.call of <tensorflow.python.layers.convolutional.Conv1D object at 0x7f13701ab2b0>>: AssertionError: Bad argument number for Name: 3, expecting 4\n",
      "WARNING: Entity <bound method Conv1D.call of <tensorflow.python.layers.convolutional.Conv1D object at 0x7f13701ab2b0>> could not be transformed and will be executed as-is. Please report this to the AutgoGraph team. When filing the bug, set the verbosity to 10 (on Linux, `export AUTOGRAPH_VERBOSITY=10`) and attach the full output. Cause: converting <bound method Conv1D.call of <tensorflow.python.layers.convolutional.Conv1D object at 0x7f13701ab2b0>>: AssertionError: Bad argument number for Name: 3, expecting 4\n",
      "WARNING:tensorflow:Entity <bound method Conv1D.call of <tensorflow.python.layers.convolutional.Conv1D object at 0x7f13701aa550>> could not be transformed and will be executed as-is. Please report this to the AutgoGraph team. When filing the bug, set the verbosity to 10 (on Linux, `export AUTOGRAPH_VERBOSITY=10`) and attach the full output. Cause: converting <bound method Conv1D.call of <tensorflow.python.layers.convolutional.Conv1D object at 0x7f13701aa550>>: AssertionError: Bad argument number for Name: 3, expecting 4\n",
      "WARNING: Entity <bound method Conv1D.call of <tensorflow.python.layers.convolutional.Conv1D object at 0x7f13701aa550>> could not be transformed and will be executed as-is. Please report this to the AutgoGraph team. When filing the bug, set the verbosity to 10 (on Linux, `export AUTOGRAPH_VERBOSITY=10`) and attach the full output. Cause: converting <bound method Conv1D.call of <tensorflow.python.layers.convolutional.Conv1D object at 0x7f13701aa550>>: AssertionError: Bad argument number for Name: 3, expecting 4\n",
      "WARNING:tensorflow:Entity <bound method Conv1D.call of <tensorflow.python.layers.convolutional.Conv1D object at 0x7f1388099d68>> could not be transformed and will be executed as-is. Please report this to the AutgoGraph team. When filing the bug, set the verbosity to 10 (on Linux, `export AUTOGRAPH_VERBOSITY=10`) and attach the full output. Cause: converting <bound method Conv1D.call of <tensorflow.python.layers.convolutional.Conv1D object at 0x7f1388099d68>>: AssertionError: Bad argument number for Name: 3, expecting 4\n",
      "WARNING: Entity <bound method Conv1D.call of <tensorflow.python.layers.convolutional.Conv1D object at 0x7f1388099d68>> could not be transformed and will be executed as-is. Please report this to the AutgoGraph team. When filing the bug, set the verbosity to 10 (on Linux, `export AUTOGRAPH_VERBOSITY=10`) and attach the full output. Cause: converting <bound method Conv1D.call of <tensorflow.python.layers.convolutional.Conv1D object at 0x7f1388099d68>>: AssertionError: Bad argument number for Name: 3, expecting 4\n",
      "WARNING:tensorflow:Entity <bound method Conv1D.call of <tensorflow.python.layers.convolutional.Conv1D object at 0x7f1388042898>> could not be transformed and will be executed as-is. Please report this to the AutgoGraph team. When filing the bug, set the verbosity to 10 (on Linux, `export AUTOGRAPH_VERBOSITY=10`) and attach the full output. Cause: converting <bound method Conv1D.call of <tensorflow.python.layers.convolutional.Conv1D object at 0x7f1388042898>>: AssertionError: Bad argument number for Name: 3, expecting 4\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "WARNING: Entity <bound method Conv1D.call of <tensorflow.python.layers.convolutional.Conv1D object at 0x7f1388042898>> could not be transformed and will be executed as-is. Please report this to the AutgoGraph team. When filing the bug, set the verbosity to 10 (on Linux, `export AUTOGRAPH_VERBOSITY=10`) and attach the full output. Cause: converting <bound method Conv1D.call of <tensorflow.python.layers.convolutional.Conv1D object at 0x7f1388042898>>: AssertionError: Bad argument number for Name: 3, expecting 4\n",
      "WARNING:tensorflow:Entity <bound method Conv1D.call of <tensorflow.python.layers.convolutional.Conv1D object at 0x7f13700aba90>> could not be transformed and will be executed as-is. Please report this to the AutgoGraph team. When filing the bug, set the verbosity to 10 (on Linux, `export AUTOGRAPH_VERBOSITY=10`) and attach the full output. Cause: converting <bound method Conv1D.call of <tensorflow.python.layers.convolutional.Conv1D object at 0x7f13700aba90>>: AssertionError: Bad argument number for Name: 3, expecting 4\n",
      "WARNING: Entity <bound method Conv1D.call of <tensorflow.python.layers.convolutional.Conv1D object at 0x7f13700aba90>> could not be transformed and will be executed as-is. Please report this to the AutgoGraph team. When filing the bug, set the verbosity to 10 (on Linux, `export AUTOGRAPH_VERBOSITY=10`) and attach the full output. Cause: converting <bound method Conv1D.call of <tensorflow.python.layers.convolutional.Conv1D object at 0x7f13700aba90>>: AssertionError: Bad argument number for Name: 3, expecting 4\n",
      "WARNING:tensorflow:Entity <bound method Conv1D.call of <tensorflow.python.layers.convolutional.Conv1D object at 0x7f13700899b0>> could not be transformed and will be executed as-is. Please report this to the AutgoGraph team. When filing the bug, set the verbosity to 10 (on Linux, `export AUTOGRAPH_VERBOSITY=10`) and attach the full output. Cause: converting <bound method Conv1D.call of <tensorflow.python.layers.convolutional.Conv1D object at 0x7f13700899b0>>: AssertionError: Bad argument number for Name: 3, expecting 4\n",
      "WARNING: Entity <bound method Conv1D.call of <tensorflow.python.layers.convolutional.Conv1D object at 0x7f13700899b0>> could not be transformed and will be executed as-is. Please report this to the AutgoGraph team. When filing the bug, set the verbosity to 10 (on Linux, `export AUTOGRAPH_VERBOSITY=10`) and attach the full output. Cause: converting <bound method Conv1D.call of <tensorflow.python.layers.convolutional.Conv1D object at 0x7f13700899b0>>: AssertionError: Bad argument number for Name: 3, expecting 4\n",
      "WARNING:tensorflow:Entity <bound method Conv1D.call of <tensorflow.python.layers.convolutional.Conv1D object at 0x7f1368119fd0>> could not be transformed and will be executed as-is. Please report this to the AutgoGraph team. When filing the bug, set the verbosity to 10 (on Linux, `export AUTOGRAPH_VERBOSITY=10`) and attach the full output. Cause: converting <bound method Conv1D.call of <tensorflow.python.layers.convolutional.Conv1D object at 0x7f1368119fd0>>: AssertionError: Bad argument number for Name: 3, expecting 4\n",
      "WARNING: Entity <bound method Conv1D.call of <tensorflow.python.layers.convolutional.Conv1D object at 0x7f1368119fd0>> could not be transformed and will be executed as-is. Please report this to the AutgoGraph team. When filing the bug, set the verbosity to 10 (on Linux, `export AUTOGRAPH_VERBOSITY=10`) and attach the full output. Cause: converting <bound method Conv1D.call of <tensorflow.python.layers.convolutional.Conv1D object at 0x7f1368119fd0>>: AssertionError: Bad argument number for Name: 3, expecting 4\n",
      "WARNING:tensorflow:Entity <bound method Conv1D.call of <tensorflow.python.layers.convolutional.Conv1D object at 0x7f1368195748>> could not be transformed and will be executed as-is. Please report this to the AutgoGraph team. When filing the bug, set the verbosity to 10 (on Linux, `export AUTOGRAPH_VERBOSITY=10`) and attach the full output. Cause: converting <bound method Conv1D.call of <tensorflow.python.layers.convolutional.Conv1D object at 0x7f1368195748>>: AssertionError: Bad argument number for Name: 3, expecting 4\n",
      "WARNING: Entity <bound method Conv1D.call of <tensorflow.python.layers.convolutional.Conv1D object at 0x7f1368195748>> could not be transformed and will be executed as-is. Please report this to the AutgoGraph team. When filing the bug, set the verbosity to 10 (on Linux, `export AUTOGRAPH_VERBOSITY=10`) and attach the full output. Cause: converting <bound method Conv1D.call of <tensorflow.python.layers.convolutional.Conv1D object at 0x7f1368195748>>: AssertionError: Bad argument number for Name: 3, expecting 4\n",
      "WARNING:tensorflow:Entity <bound method Conv1D.call of <tensorflow.python.layers.convolutional.Conv1D object at 0x7f132c1f5cf8>> could not be transformed and will be executed as-is. Please report this to the AutgoGraph team. When filing the bug, set the verbosity to 10 (on Linux, `export AUTOGRAPH_VERBOSITY=10`) and attach the full output. Cause: converting <bound method Conv1D.call of <tensorflow.python.layers.convolutional.Conv1D object at 0x7f132c1f5cf8>>: AssertionError: Bad argument number for Name: 3, expecting 4\n",
      "WARNING: Entity <bound method Conv1D.call of <tensorflow.python.layers.convolutional.Conv1D object at 0x7f132c1f5cf8>> could not be transformed and will be executed as-is. Please report this to the AutgoGraph team. When filing the bug, set the verbosity to 10 (on Linux, `export AUTOGRAPH_VERBOSITY=10`) and attach the full output. Cause: converting <bound method Conv1D.call of <tensorflow.python.layers.convolutional.Conv1D object at 0x7f132c1f5cf8>>: AssertionError: Bad argument number for Name: 3, expecting 4\n",
      "WARNING:tensorflow:Entity <bound method Conv1D.call of <tensorflow.python.layers.convolutional.Conv1D object at 0x7f132c173ef0>> could not be transformed and will be executed as-is. Please report this to the AutgoGraph team. When filing the bug, set the verbosity to 10 (on Linux, `export AUTOGRAPH_VERBOSITY=10`) and attach the full output. Cause: converting <bound method Conv1D.call of <tensorflow.python.layers.convolutional.Conv1D object at 0x7f132c173ef0>>: AssertionError: Bad argument number for Name: 3, expecting 4\n",
      "WARNING: Entity <bound method Conv1D.call of <tensorflow.python.layers.convolutional.Conv1D object at 0x7f132c173ef0>> could not be transformed and will be executed as-is. Please report this to the AutgoGraph team. When filing the bug, set the verbosity to 10 (on Linux, `export AUTOGRAPH_VERBOSITY=10`) and attach the full output. Cause: converting <bound method Conv1D.call of <tensorflow.python.layers.convolutional.Conv1D object at 0x7f132c173ef0>>: AssertionError: Bad argument number for Name: 3, expecting 4\n",
      "WARNING:tensorflow:Entity <bound method Conv1D.call of <tensorflow.python.layers.convolutional.Conv1D object at 0x7f13681fdf98>> could not be transformed and will be executed as-is. Please report this to the AutgoGraph team. When filing the bug, set the verbosity to 10 (on Linux, `export AUTOGRAPH_VERBOSITY=10`) and attach the full output. Cause: converting <bound method Conv1D.call of <tensorflow.python.layers.convolutional.Conv1D object at 0x7f13681fdf98>>: AssertionError: Bad argument number for Name: 3, expecting 4\n",
      "WARNING: Entity <bound method Conv1D.call of <tensorflow.python.layers.convolutional.Conv1D object at 0x7f13681fdf98>> could not be transformed and will be executed as-is. Please report this to the AutgoGraph team. When filing the bug, set the verbosity to 10 (on Linux, `export AUTOGRAPH_VERBOSITY=10`) and attach the full output. Cause: converting <bound method Conv1D.call of <tensorflow.python.layers.convolutional.Conv1D object at 0x7f13681fdf98>>: AssertionError: Bad argument number for Name: 3, expecting 4\n",
      "WARNING:tensorflow:Entity <bound method Conv1D.call of <tensorflow.python.layers.convolutional.Conv1D object at 0x7f1368195f98>> could not be transformed and will be executed as-is. Please report this to the AutgoGraph team. When filing the bug, set the verbosity to 10 (on Linux, `export AUTOGRAPH_VERBOSITY=10`) and attach the full output. Cause: converting <bound method Conv1D.call of <tensorflow.python.layers.convolutional.Conv1D object at 0x7f1368195f98>>: AssertionError: Bad argument number for Name: 3, expecting 4\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "WARNING: Entity <bound method Conv1D.call of <tensorflow.python.layers.convolutional.Conv1D object at 0x7f1368195f98>> could not be transformed and will be executed as-is. Please report this to the AutgoGraph team. When filing the bug, set the verbosity to 10 (on Linux, `export AUTOGRAPH_VERBOSITY=10`) and attach the full output. Cause: converting <bound method Conv1D.call of <tensorflow.python.layers.convolutional.Conv1D object at 0x7f1368195f98>>: AssertionError: Bad argument number for Name: 3, expecting 4\n",
      "WARNING:tensorflow:From <ipython-input-8-2e4af98bd57a>:246: conv2d_transpose (from tensorflow.python.layers.convolutional) is deprecated and will be removed in a future version.\n",
      "Instructions for updating:\n",
      "Use `tf.keras.layers.Conv2DTranspose` instead.\n",
      "WARNING:tensorflow:Entity <bound method Conv2DTranspose.call of <tensorflow.python.layers.convolutional.Conv2DTranspose object at 0x7f132c1092e8>> could not be transformed and will be executed as-is. Please report this to the AutgoGraph team. When filing the bug, set the verbosity to 10 (on Linux, `export AUTOGRAPH_VERBOSITY=10`) and attach the full output. Cause: converting <bound method Conv2DTranspose.call of <tensorflow.python.layers.convolutional.Conv2DTranspose object at 0x7f132c1092e8>>: AttributeError: module 'gast' has no attribute 'Num'\n",
      "WARNING: Entity <bound method Conv2DTranspose.call of <tensorflow.python.layers.convolutional.Conv2DTranspose object at 0x7f132c1092e8>> could not be transformed and will be executed as-is. Please report this to the AutgoGraph team. When filing the bug, set the verbosity to 10 (on Linux, `export AUTOGRAPH_VERBOSITY=10`) and attach the full output. Cause: converting <bound method Conv2DTranspose.call of <tensorflow.python.layers.convolutional.Conv2DTranspose object at 0x7f132c1092e8>>: AttributeError: module 'gast' has no attribute 'Num'\n",
      "WARNING:tensorflow:From /home/husein/.local/lib/python3.6/site-packages/tensorflow/python/ops/nn_impl.py:180: add_dispatch_support.<locals>.wrapper (from tensorflow.python.ops.array_ops) is deprecated and will be removed in a future version.\n",
      "Instructions for updating:\n",
      "Use tf.where in 2.0, which has the same broadcast rule as np.where\n",
      "Tensor(\"truediv:0\", shape=(), dtype=float32)\n",
      "WARNING:tensorflow:From /home/husein/.local/lib/python3.6/site-packages/tensorflow/python/keras/optimizer_v2/learning_rate_schedule.py:409: div (from tensorflow.python.ops.math_ops) is deprecated and will be removed in a future version.\n",
      "Instructions for updating:\n",
      "Deprecated in favor of operator or tf.math.divide.\n"
     ]
    }
   ],
   "source": [
    "tf.reset_default_graph()\n",
    "sess = tf.InteractiveSession()\n",
    "model = Model()\n",
    "sess.run(tf.global_variables_initializer())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "((1, 161, 512), (1, 161, 512))"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "batch_x = X[:1]\n",
    "logits, targets, neg = sess.run([model.logits, model.targets, model.negatives], feed_dict = {model.X: batch_x})\n",
    "logits.shape, targets.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x7f120271ab00>]"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x360 with 3 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize = (15, 5))\n",
    "\n",
    "plt.subplot(1,3,1)\n",
    "plt.imshow(targets[0].T)\n",
    "plt.subplot(1,3,2)\n",
    "plt.imshow(logits[0].T)\n",
    "plt.subplot(1,3,3)\n",
    "plt.plot(X[-2])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "\n",
       "                <audio  controls=\"controls\" >\n",
       "                    <source 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\" type=\"audio/wav\" />\n",
       "                    Your browser does not support the audio element.\n",
       "                </audio>\n",
       "              "
      ],
      "text/plain": [
       "<IPython.lib.display.Audio object>"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import IPython.display as ipd\n",
    "\n",
    "ipd.Audio(X[0], rate = 16000)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "minibatch loop: 100%|██████████| 681/681 [13:05<00:00,  1.15s/it, cost=0.539]\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "epoch 1, training avg cost 0.607221\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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/gtL9mvmqEM4t0cQyPaGpOzE2C49+LNFpwWQhLlRUzQCnhDoRkr0amyr2n0qpNwrCazHT05bWVcX+EzFlG2wUwLkmRU9o3fAmthjHvK/JdmvmKyFVFlE/kx1mnG0Q+JRMHDD60BrjMwoTQ+uaY3pKqJoJ+ZLPOAdzGDyuadxylCspZVujKkfZDImmliDVBHODzUKwDhbpHRcGKKXY+umnGD0MpmFQpcaE3sWoM03Rc+y+J0CXkG47qkaALuxhTdrbyZFRWLHkc1XioI5l4TtFhDNHviw0WjmTU4qoUTLSGekdxex8hbwRYlKwoaPoKMQG6NKBwHgjQBfetxIDZUuYbAQku97pnp5IqVPv35U9y34bwrEw3fDVmShhdsqi54LUQjTVWC0ULUVQOPKuRqeKeOQhDSZWi4pKv4rEQL4iBGfHnO6NuJqscBD4eGLdcFRdgxhBTxVlB6Kpos6Uj1XeR46EwlRe03xlGxdobDtFHUwpN3qEuzNcqIlGGVthl6wEVUV0dn3Ja+u6pmo4mrdq5ssB7Ssznw/LIkwzQhZOqKoMalIyebRD+pXcT2rtz52iH1M1NeMNhS4g3bMEucUpQeeW0dkAVcHSyxP03gTbyZDaYhoRelIgeXVozoux9woCawNhAKwy2WqyudGkfwuyHYsJ/ZY+ORn5xOmeJdmvCYcFGOdLc+8jR0JhVStk9z86gVN+NaiqRZ0KYhLEwfCJmr/y0d/nq4PTPNbe5v+7+BR1qYmziqrSjJSlmY24+nqfxs2MYOaYnParyobOR9zbCWouqDJDF0I09NUrJnNUpwuWl8bMioiDQYqKDatLI3bGGXWt0dqy91xM56UmdQqqXlx3MyPZg3DsDQfwNWG4BSgHGDwp/NiPfImtokVpA55/6RGCoaLuK7qrAyqjGWw3IIbOV9uIhfraMcztgZIjH+koTzS48bMfw4VgEkedWVzokFJB4Fg+t89vPv1/cMM0GduEX9/+CEosZ9IB+1UDhWM9HvJrr30Yd7nht7zzU6o8IGmUiDji0C+Lsg6YDhNUYLGlJswqPnjmOp/oXeB6scRm0WE1HlNbhUGxWzR5tn2df37lgwxfX8J0al9uVCnQDj3SRAcKqX1GXAyH5UZOwfInNvnFx36D90Yhn5vH/KNbP8ilvWVOdYZ8aOkat/IuANcnPa69eBKphfLn71+BeWRXmF5bxWxtv+3r1dNPIDc34cQq5vVLby0ifwdRWYYrSxCFq8pv+vrg7Gns7j52OvVPfGPB+rsU/fgjmK9fIjh3BnPrDipNMKMRenkJs7tHcO4M9fVbYP3Z9U4r7JsqTET+KfAXgW3n3NOL5/rAbwLngKvATznnBiIiwC8APwrMgL/hnPvqN7uhTrLuPnr+Z5Dp3McQywrbbaDmFTYK0IMxN35ig2zbGwPB3BLOFoZBYZkvBUQTS+PCvo8nRqH/SQKkMlS99O7NgoVgXGCTAD0uqJYzqkZA2daEU0vRUcRDiw083USQW0ykiA9q4tsTHzNUgkzmmNUOalJ4o0MEqQ0u0N6BtguOjpMd6jRg/4mQcOzI9gyNSyOK9QbiINqbMz/VAAvZ5QFS1Xzh5q8xzO/8iUNTvwL88Dc893eBzznnHgU+t/gb4EeARxc/nwZ+6V2Mf4+IZBEwJQxQwwVyKlAU55c9r0VDqFMIJ/aQxMQGgqodVbYoU01jP2FF6QEzzZhgWnmr0DhMrKhbMXp3TN1OMKEivTXxhkJpad4sifdLTCREY4OJPDkL1iHW+hxXI6Y+1Ucqg23G3hp0DttI/WOtveKUIvr6bSYnAlo3DfHIonPH/HQLGyucFjY/3iWYGsJxheQL5b/DGnpXW6KInAP+zZtW2NeBTzrnNkXkBPC7zrnHReR/Xzz+9W983TuN/+YtUYIAV9ff9JreLLrdxkymh1vK297D3XHftK1JGPmtccHF8WZRjca9rfDN48Qxrij++LiHb/zjY32r8t0I/q69SQl3gLXF47ejLTr1dgOIyKdF5Csi8pWKexPwrSoLwIxG33SSDsd90xf08Bx7m/e+nbKAtyjrLeMevvHbU9Y3k2/bSnTOORH5lk/itzDhtE4586FnAXyBQlNjAyE6qCk7AVWm2P5kRbQZHiKkdO4Dv3UimMT7Rr0LFTq3mFhRdDRVUwinDl36ADFAcuDPqXBqicYelbX/lEdHRQPBaQhmPvpRtRzJnkcVx3uO3qWcohcuqBmEcGJwSlDGoQuD1O6QX0qsj5ZMziTc+YQl7s+RV1u0rrjFfcLspNC46ZidEEziOPGFGl0Y+PJ3Hvm7JSIn3rQl3jXn3hVt0R+TaU700lVQGjedEhmDOncad3OTdGUJe2ebpc9kTD/2CPFugX75MrKxjnntIrrX8/REa6uHdEWuKEi1xo7HBKc3qG/cpHN6A7TC3tkmKwpvmV25RgR0ux0IAqr3nCH8o6tIswFVhVvqIqMprpliXrtIsL5GMJ4gaQKioNeG/QNcUSJB4CP2d0UEyorexYTeZwrMwRD1vidQgwluNsOdXsf+E89IuLK4B9VqIVoh8+KPz9HdYf+EZ9j/Auw55/7egsCy75z7H0TkPwP+Ft5KfA74Refch7/Z+MeO81vl23KcReTXgU8CyyJyE/ifgL8H/J8i8rPANeCnFi//DF5Zl/Bm/c+8mwuUJEaffZh6peW3mMpQ9GKya0NMM2a2kbH9rCc0aV13JAPDvK9pblYMz4ck+57wJNu2pFs5qjSU/YT49oTpw22iYe2zAIu7jYY1OKgzn2LZf7pF2fYFEb0L/gyarmmCuaNxp2Z0LqB7sSTenTM73STeL31GIdMEM0O4O8GFekHpJ8iCjg/ApiHXf7hNNPJw7JWvFYiD+UqILhyTU5p01+IUtK7lPh754v3zYUfCce7Ea+5j638Vl8beHG9m3qRXgtMaKUrMxcvUP/gBxmcieq9OCG7sYJe6uFCTn8iId3NcoAje2EREcP0OTvlzq+4mBJOSqpcQjAr0YIrNEu+nlTVyewd7dp35iQbh1Csz3J1hX34d99H3E+xPqVZbRFe2PS9iHCLGYvpN9PbQl76Wlb9mgDjy23OgcVFIvdKi7IaMTwW0r1XE23P0zgHl+VVstLjGTNN8eQsXBnzx6q/c1w87GgpLTriPnvnrHpsOsKC0c3GIFBXFiTYHj0beGIi8gaGMI5w6ZiuKpZdn5CsxyW7pI+i1xaYh+tYu1fk1bKQpuwGqdCQ7OXpzH7vcQYqKut9gejJmclLT3LTEBzWz1WABV/PGh6ph+cv7h5lw2dzDnluH2oIW9N7Yk2kuiDlxzq8UY7CtBnd+oE+ybxeJUEd2O2d0PqVq+EKO5q2S5Oqex9WXlXecy+2jG0vE1LC9h7RbYAyuNlAUSBQijYzw89dZ2zxD3W8gn/8a6v1PwuWb1N/3CK3fu460W8gXrhI8dA57ZxunNbrdgjRBf+0iQatJOBzhjIWnH/Wm/cVrcGIVPS3pfnmf1nIbdTD1KKqPPEm0PUUNRuSPnyD+ykXYWEeNcx+FmU7hhdeQIEAaGYQhFB7AetcPc9Z5ZNSdbU6UFebCGwQbp3yB+8Mn6L4+xiYhdSMg3pp4XP7mtv+yvsMiOhIrrNXdcM9+7L/DxL6YwIQ+kRmNDLOVgLwvjJ6uQBzJ9QhVQbLnqDNP0FUs+Xto3BA61ypMpJgvK0wsi9Ih/ztfEpq3fD4KgWhsyXuK6SkhHtwlC+OQ7dSkjnAkHoyaQveSoWyqQ9IyJ3eJxuxb6pp9vs0nUQ8eDhk+XSGpQW1HNG4oXyTYEWbrDl2A1EIwg95F79O9+Du/wPjg7YshjsQKU4Uhu7CDS2Ns5ON/aMFFAemVOXsfXkFeCokHDl1asu2S+XKI7PmIuLoMJhRaVyaovELyivBc77CipOyExIOSfDkiXVCl3cWLqDNNnFIkB17pzRs5B4/6THT/9YI61ZQtTfeFHR+fTEPqZkh8bd+fXdP5vTPXeiyHU+J/hwF5b4XoCwHztZDWdUv3s68x+sHHSAag54rexZKiG5BtemMJ41DFO0RsjsoKe/8P/vfYQKgyhS79qgjmlrLlK/Z3PmzBCC62xNsaVQl6DnXDswiku76ENh5agtzHGOfLinjon68yfybVDV/Al+4b8o72K7QvTDcs4UgIZn51W+3PLhP7JGgwE9afL6ja3qm32q/uaGoXlqHnAb67Ou+mWepE2PqIYFdKwmsxwUxIdzxy6s5zCgGiA+/8dy/4Qr9X/u3PM9m/cXSNjmM/7K1yDCT9HpJjhT1gcqywB0yOhJUoSUxw4gy2nSGVwbQS6lZEtDWFQFF1E/aeTjCxP8yXXvX8wLNlRTTxPBpBDu3Lc6Jru9h+i7qboOY1xXKCqh1FNyDdLj09UjsknNUEgzmzM23yvqboCNHYw7/jA2/sxCNv9gdzR7Zdk9wcUXdTXKjQo5KqnxDtznxytKrvJWKtLyqXqqZe77LzTIOiK+gSOlcMTrwDbSLlsw0xJANL6/WhLxK8eP/qlSOhMBtpZo+v4pRgUoWeW6qWxkQtbCSMTwWMzzps5GjcUGw/EyHWpz/yud8kghziYUTdWEeMo+gFVFniowu17zChqpA6udu6AUZnepjId4cwieeOsiEUHV8RefCw9qmbUhAbUDV63o2oHdWpmGDuqJotgukCl7goMBTrO1ughK0PRhRLFicOVYsH7DjIl72VWTUd0UgoWxoxHf/eG/q+c3UkFCbGV+ED6NJDneNBQdUMQSl6l0rqZkTR9wRfvQslk1MRbAHO+YpJA/FBhZTeF6paAUHuaN6Yg4j3wbZyZidTwlHtQ1szRfN2jYlj6hpWX8iZrfkvQzg1uJse5z/ZCGhfnnmfrhcRjmriPYdJPEybu0jfRT8WgKCymFjTuh6QL4POhaWX3WJsSzQW8p7nGWlsGpyCdLvA3a3gvN9cHZv1R0+OzfrvITlW2AMmxwp7wORIGB2232DyQx/xTXJiH8tzylPgOQWzk46zH77JnVGL6TBFBiFS+/gc4wDXrCHXdF8K0IU/2Oer3goT5+N7TnnWT/C0RKry0fb5CYcqQb9nxGynQTDSmPUCN9ek10Pmp2vECMkdTXbHLcqK7h0vyb6vtIR7TXLuNq1zCu583LF6fg/rhMGwgbudoOeeIbU+UYI4nFGE2yHtS4v7/pd/ys1yvlXRc0Pn5X1wjmqpgZ5WVP2EcFRStSKS/ZBrboN4IHDGEB0o0m2HfjWiagk21JgYOlcqoqHvchfOEpJB7fu5yF0CFkW6a2nczDFZQJ0qWreE6aomrzuEiaNxW+BawuS0I9l3ZHc0dUOIDxy9V0bYJPTX2QoxiSLZKQgGM598vdtdsKz84zDAyRL7gxWqtiXZ0rRu+FLcybpmXsbEB34OoqGjc6VArEPnR50c7NhKfIscW4nfQ3IktkSyBPXYk7hA+eQlC86pqd9a5icypquabM/nsJq3SkzqowHh2BeY21jIbs4wjZDgIMfGAS7U6GmJVIbZ2TbZxT1cGpGfaJLeHPsqynHO7FwXVXlnu3FzRr6cEB2UTM6kpDsVNlKHQFFVGZwINtFI7VkD9LQ4RE1RW+9Ah/76yqWU8UZE5405042EzmtDXKiZnmmQ7JWE2xOc1sxPt4hGvrCdl48415QLFdPzLawWyqbnXvJVjjFOQZ15bsE9gKBmbxySbitmG4ZwGGNih9RCPGjTumFRqxHzJbUINWXEA8d8VZCn1glmgMB8pecTpo0WRRfmp2vUXNDzJuI8V5UuBKkjzzBaBfRfWfD/zn3oqegKycCi6pRg7kE2uHtJTKeF2bJi/1nD+C8atB4z/ErPJz7HcPOHQvR0CbGCiR3LLwSIBXPpqIemakeyXaAqi8kC9KgkP5mhc4sq/Te/bIW+wLwDa1+pma4KjVteuXnf4ySWXp4tqCNAmehwfBMK7a+U5EshVSYkB+YQal22FI0tmIwD0h1L1fRkYo07fqXkXbWYYEeyV9G8UVO1wgVUQRFvzxfEX/faAt9tF2wjjZOY9GaAXGvhBBq3HeHUMlvRnPkMzJc834cNhM4lD1/Qxf2NjiOhsDpT7L4vwwWeSc2EKapmcSMwe6zgP3/vl7k0XuFUNuR3H30UgCiuiAJDI6wxVgxVPWcAACAASURBVHHl/BLZlmdzy1cdUkPZN+ipwjQWWxaOaKCR2gea66YlWJnzxIlt3thdoioDOq05BDXTMmQyi+m25mzvN2l+NaVqxoeryGlHOI4IJ/faAnuOEX/tTuDgvZaf/NgX2Mzb7OZNXr+xjpsFqMac1o8fsBwV7M8zxpOUst3yO8rrDwib22H5DxxWJ775uW8qf8IKyfuJ7nYwB8N3/sgwAmffWsWySLPIoh/LtypHvsbZdjPyj3sIftVUlA259y1VMD0ltD68w96giZ0H6ANPxWDPzXHbCbZdow4Cuq97KnMTCrNVBcqDaMBH83Xut9R0xyu1aghVC89nGPp6ZRs6XOgO65QRkEKRbila1y1V5qtnTOyvLxo7ook5XGE2FFTpx3cB3P64Ijo74UR3xOUbK4SbEboQqqbDnchxtcLlmngroHvBI67sbz2ANc5/nuXYD/sekiOxJdLKqD7yAZ+JXQp9k4HFwW5Czztlf2KP/VtdiCwyDgimPlbnQocqBJ0L7auOdG9B79DU5D3xOPwaio74DHFLaGxagrnz2yYwWxfyEzXRnkaVHumbLzuCuW8d4gTifWHla4uODwrKlkbVHvWraufbjyy2ReDQWpycjNh/D9RrJZSK5qXwkEtq8nAFAun1kKrpWP8Di9XgPnvc3eiBkiNvdEgUoc895FkExLezsEmIPphBGDB5tMPuewP6rxnGpzQrL+bUqSYalpS9CBsKdaJItyviLd/Br15uEVzeZPbsWWzs8fq6cjQvDrFRgGmE6GmFaYTkqzF519M9+B4uDpMowlFNdFAweqTpx76+j2sknuKhrKlWGgSDOWpv5NkD7nZ0CLQH4ijF+H1rjE8H5Euesa3/WkE4mJMvaB+CSUXdDIkGBVJUvgPFpWMK2QdKjo2O7yF5NyWzp4FfxVM7OOCXnXO/8J1kw6lXGuz9+Ed9DE7u9e7SBVQNmJ2r+IkP/iG/feNxPrh+g9+78jDWKsKoJgprijKgGMck1yPigfe5qhbM1yzBxHMTusi3ow+mgkkd2aaiTqBuOOTslFNLQ7ZHTWa7Ga21CbNZTBgajBGaWcFwlNH5fELV8JA48LMRjSGYuUNO+rukKHfjinsfMPylj3wZgM9ef4LJMEXt+Phk+9EB03mMs0KcVKj/4Hmn6l/7NvywBUvACefcV0WkBfwh8F8AfwPYf1Nhes8593dE5EeB/5Z7hem/4Jx77p0+43hLfKt8W0bHgkBlc/F4LCKv4clSfhxfrA7wz4DfBf7O4vlfdf6b8CUR6d6liLjfZ0iaoB55AnEO04iwkUbnNSb1tcSqslz7kdZhIV/vQoGJlU97zA02UiSbM9CyIEkWbBRQtzydrBiPIQxHJeGVLWbv20CMI7kxpFppMjuZUHR85B18I7l0t/ZR/aWAbLtGlZZo2yORTepN82Bv6imLWon/nKLC3a1vAx+iur3N9n/1BNMNoXPR0rxVYiPPOpr3Nb2XR0zPNXFKaF72JM28/h1KryzoH54BnudbZ8O5r8Lqhmb/md4h9sJEHoWrar/6x+dh+b1b7A0bLPXGvHFzCZRDxKBCi90NcWlGdiUk3fUYjbKzQPMuttl8xZJuNSh/7DyqhGRXMM+s+jYaHUfy2JC9g5RgJ8I0LNTaB5+bNY2lGfVLHVpXI0ziQ1qqBhs0iEa+F4zcrcF7c0jLOg5+aolzH79GVkXcOL3EVhWgJ4pwosg3SrY/leJyQCzLz3c8ZuTadyC9IiJN4P8Cfs45NxK5t2L/JGw4IvJpPIEYUdYjKDyrTZX5cXXhz4WiK5jM8HBnD4DSaLACRlDNCmcFWSrACuJ8DxST+JhhnXluX1UI8a6i7PheY/Ee2MhnApyGul+ThDVF4jEgKCA2uFohoSXPQ1S8OKe0jyWq2iHGU5sHubvXb4W7xYCLtsOPzNkat3h8eZtbcRe76BdmIkeQ1dSFhsiiY0OdhN903t6VwkQkxCvrnzvn/u/F098WG843UhclexU6N5TdkDpRxIOaOtNkO0K2pXjh1lMo47/JSdPnlSanA7pfd0w2FO2rFnGWbLPARorWTUWdqEUvaJ9yiQc1o7MR2a5BjGO2EtDcrNgpItyXlugsoiuqBFUrBk8I4TQg3neHvL/T0xmq8gqykQ/0hiMfAREHLvCtPWzkG5fWv52AJDz/sSbZGxHhFDpX/Ba7Nc9YfsMyXVeEE0frVrXIan8bUO2F1ffP8AbGz73p+e8YG86x0fFW+XYjHd8P/HXgJRH52uK5/5HvIBuOhCHBmXOeVCsvsZ0mLtbo7SGEAWapxXw9RReW6XrI0hfuwMGI0Q88Quf5mwyf2yDZr1ClJby1j2ukvu7YGG8IaIXtZL7ge5rf43IKNE4rxu9dpfXKLgfPrNC4lYMWylaIOEd6c4LkFeWJNuHuDBSeiOX0Oqqs741V+RimS6LD/mEA259Yo3cpx2pF2Q1I7+S+PAkYP9QgyC2qcGSXB7g4AAty4ffuP1fHkY6jJ0c+lkgjRR5/DwQKJyy45i029L8nZzJ2nlEeBNMS4pGP5pdNIRla4kHN8FxE+5rPTEd7OWIM+cnWovlpzfRkTDT21LBiHfF+gY01JvaNUscbvt+KB9w48r6iectQdBVWC90LM0wWEB7kmKbHi5hYg3WHXWhttOjQZ51HgNWWshuz/1RM0Yfe6xZdOMKpoWpqomHN4LGI9tUap4V4UD4YqCkpK/T+CDcc4c6c8O12JzNUvwNA+6UZwbzPdD0g3bfE+zXx5ggZjLDrS+TrDfqv+UrI4Pa+Z9MpS8JmjCpq1M0dOgc9bBahpgWUFTKZ4TotouGY+s4W2WMPMz/fI/2DN2B1ieh8j+R3XyJ74iEAyn5K+Psvo0+dQF3dhOU+UeV7NTMYIkGAEsHlBdJs4GYzJAwJv7JFX32QwSO+P3S2OUdfuUO4vYN+5Dwr0yZqUmLasefJCnwrxvvO1fGWePTkyG+JEkfo8494niURbBKgZiU2izzociNl60OKpT9yzFcUva9XvmmNcT7BmQrZtiE6KNF57cnBIu3rm0tLOCo9sDSQwyaoyW55iJEv25qy6eFxzdv1Ye+T2bKm/+qMwZMZOFj9nVuYlQ5FPybenWOaEcFgjuSVZ9ROogWxtPZGSBRSrDUZnYswkW+8kwwN8aAi3Jmy+cllyg40Nh1VJqz//r5P3bx21Guck4DJk33vaCaCW1R+2ACCwoM3m08M2D8bkSQVt9e76FyoM3fIOLP3fkV6J6P/ukHVjskJ7duBONB5RL7kHV7wZbdlM6Fq+r9VCYNP5rj9mPGZgKprCcaKdFu48uOZD0orRzI84Rv5xMJsLaRqQDKIF51vF2WztfNlr4vfsxXN4FNzOq0Zu3st5CCkfTHFhinzNYeJHXVTMIklOej6wo3rx608Hig58ltivdpg+yc/ho2hbPmIgVrAJ5zA/PGC//oD/4GxSfji7nl2Jw0C7YN3zglp5F+8/UdrRAOPpJ2vW2xqkUoQI9hWDYWHvumpIhwryo5/TffEiIf7u1zcW6GqNad7vgZoZ9rAWEW/MePqpTWabwRUi+tzAib2DADhmEPr8m4c8S7/1PgTc37m6S/SDyb86633c2lrmeogAe147KFNaqeYlhG7B02iVzMAql8+6jC3xkn3kac+jRQG046ps4B4d06xnKJzw3QjYfNTNa3XIlrXDbNV7dmvp47ZupDdcYQzR+vqHJXX2HTRNK4REI4qyn5EnSqSvYqiF6JzS3prwvxUk7yvma/43NjyS77Rdjjz2HkTQzxyDB5X9F81NG7M/FmoPU3g3fZRd0UW/BwuUKh5hQsUN360jxiYnbK0Liuatz1MvHGrYPuDnjUu3fEo5aWXJzgtPP/iLzGa3j665GCdcMV9dPmnPFkkYNsZajQD8MDKVsbsbIPG1QlSVEwe6+GU0Lg+4eCJFr1//QqyvoJZahLc2j8spjPdJnrnwHdbSBNPItlIcEqhtwe4ThOcIz/dwUTe54u355iGD8JOTyVEY4PTQnZjghrNvBm/aNXhL9b69sJ5/qZmBgrRyneImM2ZfOJRGldGTB7uYCKhdWWKnhS4KKBuxaDAakV8awjG8MXrv3pfCtkjsSUSBNDv4Kra8+iOc2wrxSmFizVqUrL9rCZ8rMvSSxXB1JAvhwyeaiPOsfOXnybdt7S/uontNX1b+27qCZ/LJvONFuHEcyc67cmVE+0rN/O1GBMpxqcVnSuGyfe1cYG3FoPckvc0dSYE05R4VmDbKTbUqLxetPYw/gvSynyyWSlY+GdSVJSPrTN4NGD/iT5rXy4ouwF1M8JkIXVDUzY1JhLikSFKQpDoHqPO28iRWGHHRsdb5cgbHRIE6G4fV1aoThtXVZitbYL1NQ97K0uK958nvnmAjKeYU8voW7vkT50iubSNWe2ib+54NmvA7uxhp1P0Uh+qGjMaEayvYXb3cM8+ibzwdSQMkHMbPvrxxi3cmXVkmuOSGLU7gDjCthqowQiX59iHTqEu3fRNDdptpN/1q2me4xZnF2W18CX9lujq2reb2jhF/tg60ZdeQ1pN3Ill5OYW0myQP7RC8upNqvPrBJc3EaWQnSNu1re6G+59n/o5cD6bqwtHnagFzxNMTgv6AwcEypLFJXdeXUWXQrVUIzNNMPetMLJbiuyOQxlH0RGqphCNHHlfCKce0CPWswjoBWupjWB20mKXy8Nq/jqzxLua/JSnGpBaiPYVSy950jAbeICQDXyb32jiUb82vIf6vQvC2f5AQOvDO1S15mC3iRoGBHNZFCo6XGyJ9nz74aU/AgRe+61/wGTvmJH0z0S+sRvSu5GjvyVGIcHqSexo7LfE6QxXFKiVJeprNwjOneHaT29w4vNzguEcNcmp1jvoUcH8bAsxkF4fInmJG0/hbj3ZyhIMhmAs0utAWWHWe97Ke+0Kam2Feq2DHhdMH+oQjXzISEZT6o0l9O4YqQ2zJzxcJf3yG0gUeSPJOdx87v+OI4/6tfYQ8Ysxnna93yE/26Vs+a7sndfGqBt3QGuqx04xPhuz9O9vUp1eQn/tIpKlyOD+mI7jFXYE5Rj5+z0kxwp7wORYYQ+YHCvsAZNjhT1gcqywB0yOFfaAydFwnIMA3V9B4gjbbaEOxpgTfdRo7gGZWtj8gR7B1Hmm7FulZ+IeF5T9lOS1W5DEuDTGXbuFardAKexKFzUYY/pt1Kzw3f8aKbMzbRovXPcxwkfPoG/vMX3/KbI3BpQn28Sv3wbAlSX1E2coOyHp9TGysw+dFgTaI7bW+qjdoY93zuegPeyNukbiyKda+l2G37fC4HHP8dj7ekH8xjZuPIaTa+Qbbd+lfWLJXtkErZCbRzyW2G6ech9+5m++Jc+UrySHpUQmVozOee9/vuJo3BTE+d5bderjcrr0HYPSrdKnUFLNbDUgGRrqxOMdfSbY/47GPmBbJ36TmZ70vFVSe8yHqv2YdSpUDc9uuv78HBcIeT8kmFnqhiI6qD2Fu/L4fTEey69qi9OK+VrMzvu1p1CaK5rXhXDs45117GOZdSaYCE58MUec48tf+d8YjW8dxxIfFDmOdHwPyZE4w2yvwew/fm5Rr+UpGu6y5+kK6gTy/3TEbDdDtyrUtRRV+RaIuvTtMFxqaL0e0rxt0aVjdFofkj0n+x77gfNpkWgB9a4zFlloGD1qULkimAlV22ITS7wdIA7KjiUcC90L99ozlm2/AKKxL0XSlW+zeBd2BwuerDXN+GNzlntjBuOM4MUmwQzKtm9F4kLn23sYaNx0KAPmHbimjoTCVGE8hHmUU641CffnmCyiWI6J9wqmpxLGF9skM8HpkOZ1R1B4UGk4dhRdRbrrUUrNGzlSGdItzexEjA2EaGQIZx4jH+SWcGxQlaXONPPlgDoRei8p6lQIp46ipwimCqch3bUUHV+4135jjskCgmlF3QixgRBMa499nC4yBNYespFKbYn3M6pmSj5PMacdq68ZqkzoXTQMHg0J5h5tZSLoXpwjxqHz+7dUPBIKk9oSbA5Aa8I9j5F3kSK7MaFYTum8uMvk1BrhxJenhlNL5w83mb5njezqiOlDHYKpIRyXqKt3oN/BdFKaVybUrZg69VaYEwjm5nDCk1sTwkmCKmrG5xsEmx6A2rtQ+6KFccXw4ZTlF2eU3YhglBNeHWJXusS7Y1wjQQ2n9/o3hwEuDJC8OkyzJBfHtNY32H9SaNwSTCSkewYbCp0rNSZWOAXZjiW6ue9bA9dHnOASrTD9NijI1zPCUe3RvyLYWFGe7BDMHUXP97GsGgo+cIIqU8yW++jSMVvR6DKklW0gpWV2MllMTk12eUBxqkPRD6hamnCsSW9PyDdaqMqy/2SK0367VJXvblQ1AALCKUzOpBRdIZxl1KfbxDszqo2eh7pFb5rC2r4F6gZQn+pQNgVVC3WK757U1bSuzrj+nzRRNcT7julagCpXfcXo5hGnkHXa4+lNGqAqR93wja8Rn3Yv+iEHjztcaAmmiv7LjslJjQ1ZFH8LOnc07ngi5boVEswtNvQNRvc/tIzVQrZTMzkVULQCXNCiThU28BjHgycdrTd8ia0B4qFv6l2nnjek/3VDnQaUbY3UCTo3zNaSRc2zQSoLofJAUnX3EHPsPp0wesIQ73gl1Il3Q/LvaxDMoG76Rqomemfq2LtyJBQmlSHcGqJbqWenrozfFqxFz1PKbky6HdK8YZmteZ+oc6X2NcSpQlWOcOyhb+mtCcHBnKqXonOLUxCNhXRzzt57myy/MEbvjTFLLQ82bUaYKKL/omBDR2PLHHaoDeZ+C25sVozOhqz9zg5JFnvwqBa6L88XWeaFa+R8q2GU8lWYWnHyc3Pa17vMVh3z5XvUErp07D8ZsPyiAYGyoQh3Z75qtLr/GXbshx1B+bb8MBFJROQPRORFEXlFRP7nxfPnReR5EbkkIr8pItHi+Xjx96XF/899J2/mz7u8my2xAH7QOTdZ0D/8voj8W+BvA//AOfcbIvKPgZ8Ffmnxe+Cce0REfhr4+8BffsdPyBLkPU97WHYc+O1wcQ6YWFP0Am59yiFWoBZaV/3Zkm06JqeFbMstqBqg9/oEqQz5Wkbd0OjcUnQ1dezp9+KhRRf2sBxIz2rufDSj6Dm6X/cwOxuCje811MlXHCsvOFpXpszXU4LZooWicT5ENioPqdD9RTtvfBjH5NEO+09o5huG9KYmmEH3ck3RUYzOqf+/vTONkew6z/PznXO3ureW3rtneoYzXEWKFLWQ2qIglmPJO2xncZDEcALHiIMAAQzkR+wgQGAECeD8ih3EPxLAQZwgseAEMeI4jhLbkm0YliKRkiWK0nAZcmZ6eqZ7eqnqqq6qu51z8uPc7pkhOcOhSHp6hH6BRlXduvfW7frqnPudb3lfggl0L/nzpes5qra3bZl9S1OiiKTAHwN/H/hfwIpzrhaRjwO/4Jz7PhH5P83zL4hIgGfJWXS3+aA3mxKDU6vUl19H9fEdi7dd5iYiGk8K9hDwK8B5YOCcO2jGPaAnghuoixpj7gHzwPZrznnIhJMEXfSDD/rSsSzxzd1KUJMSFwXsr6Rc+qcnCbcDkh0vaR9MfWA23rMUPe/dta8Y0rURAPlKho384je5VmBagQ/8Ks98HQ5rUL4taO/+GJP4KIWqveutC8jnhLjvIxjKwPwzfapF37DhlI+cRDsT7yRU9WF5m1jnswzWUq7OcPXjCXXmiPtCZ82iS+94DO/zX//B/7L4Fd8AIs+8zaZ055wBPiAiM8BvAo/eyXFvcs6bmHCK0zOH6qy6shQzIcE0ouxoyo5CjzztkIl8NfABBXmdCq0di4l8BP+A6bNq60Pu4MmJhDrxihBlWx/2b9UtQRkf8Uc1U5z1mmAmFqKhpziS2lMplUuZFydIFEFu/bIgaqNz06hBNKoQTcRejGPwUEy+aHGRIxzpJuTmqd6DsZ90VA0BjqobNuIKt3Yt3pJb75wbiMjngY8DMyISNKPsRnqiA+qiy82U2AMvm3IrSGmI1wa4KIRAYSNNqzDYWNOaGrK1GjFtbOAXz/Geo7NWMLwvJtz3vPE2FML9mmBniliLns8wLU0wrlGTimo2QRkLFtJX+thui6oTIdaRbJXsPZBQtYXupYrRakC2aUhzg64sdaL9InlYoHNNa+IjGXU3Idyd+H6w0fS60IFrRlgY0JoL6X7WsPVkRHvdxznTjYI0EHYfTZh/bsJ4NUEP3PV7o731bepOvMTFZmQhIi3g08C3gM8Df7XZ7W8D/6N5/lvNa5r3P3e7+xfg/8ndAWpngBrso4qaYG2bcGNEeO6yzzVpWPrDq5Q9/FR0ZUi6VTPzrSGqsFQt5X/dVY1MclRRE+3mANg0JN4YUWUBrbURxWoPqQzxuhe6VpUh3arJNgzJ5RGd9dqPmkAR7BW0Lgx8jmswJrw6QKYlMi0JRgUyniJXd3D7E98MkRc+rzcaw7Ud0v/+/9h9T8TsyzVVJrS2PReH1Q2j94mEuF9jQyE+f4344g5SVrf8qu5khJ0Afq25jyngN5xzvy0i3wQ+IyL/HPgq8KvN/r8K/CcReRnYBf76m35CoLH3n0RNSqqFFDWtMWcWqdsheqlDMCooesIrP3nSU+cNDHvvX6DMhOF9PbprtW9Atw6XhNh2jG0FTBci0o0CPS6ZnO0Rb+eMH+w20YmI6f0dwlFNMRtSpT7JOXhyhmhoMVlAOLbU7YjBB3vMvDSlXuriQoXVyo9WQNIIp4VgmOMsoA+Evf2jWlmks25Y/y5F70VQ05rxKU8wluxeD2OVbUX5wCJYcJu3ZnW7E4LLr+M5El+7/RXgdaRfzrkc+PE3O+9Nxwh+GtGCKgwqr6i7CSbyo8YFQtX2rNTjVZgsaqKRJd2yTBc0+ycC6lQ8n9NCSjDykXOnwCQaGyUEE0O+1KJse/ZsnEMXnnO+/Y0tLv74CXQB89+sKGY8V2Lr5W0GTy1jEth+f8rSs/sE1/ap5zL0Xk65nBFvT7CtEKc1RN5ILlCovMYFiumpNuMlxfIXHU45dp5s073ghcPDqWN0SjF3zlDMCvq50ks23gZHIoEpDqSscaHGJAGmYfhMLw0JhyXjExGqhtaOIxwJncsViKdfOGgE17lfV4XDEpX7KSXue84Nq4WwP0VVlnDi0KWl6kaEI9+Vufk9K8R9x+yLjdPrIN6t2PoLK1SZkPR9nFL3J5TLHVwgmE6MKgwmi5CyPuzElNqiphU0j9FeRTEr9B9VZFdLWrsWXVmifb8eNC0oZjzFHxZUUd/2HnYkYolOCS4OobYE44p8ISGYGmySonKDCYXx/TX5oqK1CXtnvTd1EAFPdl2z4BXvYYUxdSugThVV6g1mY3XIM+UEnw/LAoZnAtpXDNtPBARTH6DdPyWEJ2Kyq5b9VUU+L/ReMdTzmSeydA4XKepWQLjncHHoZwnAhZ7GVjDYQDO6L/YKF7FjfCKiagt5L/FR+zlBlTA+ocg2rCeUKX2m4lY4jiUeQRz9/rAwJFhc8aViJ5ehrLC91K+LpiW2k3gqo1bI5sd6LH517HvD7usQ7xaMT7XonNtD1jeRXgeqGrs44+8lDQWSGk6R2mB6GWKuh5ZcoDBZhEkC4s19v+/eBBeF5KuePDnIDeHWxJe5ddu4LPGe4v7ER+ujEIrS940duPbGQBQyeXSZshfgFLQvThFjEetQa9eYfvAM03lNsmsIRxXRhS1fQnf51vex4xF2BHFcNfUdhCMxJdYLGTs/5pUh6lQOK5qCKSAwesDw9z75OT6/9QgPdHb4wpWz5GWIUtYLk5caEaivpHRe9QnN6ZJPSAKYlsNkFil8VZTOhWAMpgVl15E9PKAVVfRHKcYouu0paVQxKUMmeUQ3y9lam6X3fEA54+OMdepjj8HEq5wD1ynQHV44tYLtD1m+/+NfYzEa8fzwBM++cBY1CrC9ms7cGC2O4bCFLTSdb0VIDfV/PuJVU0HhmH0x9+5y5Ad9MRMQ7ZvmtebXTnyU8mKbF9JVuucCwgBv2Azi3EscnnymAlfjAiHpa6qWT6nUseC0LxcIJw4TOeI9hw1guqiwm7PszjVxxJFQSso0gtkXLdITRisdFtYc6VaNiYUyUyR7hqKjaV8p0dOG6LLBodKsdYzOpHz2i+9n5syA4Uuz9C4o4oHDhiFOe+mOdiqYFnQv+nurLt5GaOrPBM75X2RuQLzAQDi2mEgRjmqyq5bpIMEmjnDver2h003OSvsI+2jV3/SDsafgS/YsVvsAr6o4FC7oXvJrnXDiSK9Z4r7zhGSlEO35kjMbO8YrimLGF/4c0OsFU0uyZxAD4dQe/sAOxVKdA9uUnDvH6h/luNjS3+z6kvLCUWU+E1BlwviEr3PsXLQk2xWtjeK267Bjp+MI4t5yOt5g0SgffPzm18GtZ3KVJK/fKPKG51Vpil6YB6XR3S4qTQ/f090uAMHqyTu98jfE5C/dWidIz8+95fMdiXvYTXiDEa9evcyNdUS300a2eX5H5wSwkwlMfNLQDIc3vXfwul6/8iYXfHt0/uRVblUDZXZ23/L5jt4IewO8mfj1UYbZvPbmO70FHIkRZmcyxp/+qI8pKig7/kYvBsKJpf+IJvxwHyWOogrIr2S42EJkoVbeXR8p4h2vIItAPqcOxdeqNpQzjmRbCCYHxTM+k1x1heF7auZWB/Qvzvr0RmyRUuHaNTIJIKtJzsdklz2vvXccBBsJ8cASjm8ewXLDiB6tBgQ/sM3efoI1GnUpOVRCkkf2KTdTXOCQUrH0JR8It79z1BlJj52Om3BvOR3HuC2OxJRImiCPPo5NAhAwSYAyFj32vLnXPtRGrI9eRHsw+3LFdC5Al75f6wCdywWq8FVL49UWre2S8UpM2fGi2wj0Xp4ghSE/mRLuVbhQsfN4gtSOcOLXW+MTimTbUfYaOnMlLDw/PeT3rbPAp1mUr2sM+1NsFFxXCJSmICdQrH1vYHwLiwAAGD9JREFUFxND+5LDJOI5f0PfXlt2hHTLUPQ08dCQrk99euhrf3LLr+pIGEyMRU0K9N4YM5uhh4WvYqp9r9WJ391g8NQS2aalToSip8k2K6wWqo6mfWFMvtwi7OeowT4oRbsymFZI59UxLlDUaUC0k2OTgHo2IdyrCPtTKEoWqp5vJ5r4+vz55wrirQnTk23KnibZLgm3xl4usawR28LGmnB76hOXtUFPCx/tEPHUss3i98yvXqN44jSDhyLaVw3iHOnVkqoT0H1xQt2LiXcr6lQjZU0wsW+vCOfPCjLJceOJT4NUNVLUzfaC4vQso1MKcb6JL9mpKXqaZDunbPtq4ez8gGo2waUJrhHwRgsooU4DwmGJaUfYWCPWEV0ZYFsh1Qmfhtm736dA/EgOfUXUfk2yWzM8GzF4cg65vAnOoUpD2M99hnl/guRFU952Q/dJWUFVM/7IWQYPRT4stu8b5MVYsueusvXhLoMHY0ysvMEO+srsrbtYjp2O20DCCHfAvfg2oBfmMdu3rfS7CUc+gek6KeUnnkYXlqoTHKbyVemwsSA1XPoxC1ZIXw2JB75S1vcoQ9AEf9MrjvYVH/ytW748IJh6XZNw4jCxUKUQTiAeGqqWosp8H1qVerrZ8Skv+eFHG8y+WLP5tCYYC4tfrw5pIupEfF1G7mWzgqlvU1LVDVIeCmys2Hwq9HSxoae5bW05TAxVR9i/z5Je8ZQTC1+vfVL1j79wy+/q6I0wpcEaVJpiJ5PDx+DMaajN9chDs9/tcDBCDkfKQXjqDv7ng2NuHB0qSV4XSTngqn/d4xuMzjsdsUd+hN2Exgi2CRkdPNYX195wv9vh4Ms5/JLewo/z4Jgbp7I3CnsdhMle9/gGhnknptcj43Qc485wbLB7DMcGu0N8O6mQdwPHBrtDfDupkHcDxwa7x3AkvETRCtXKkHaG3dnF1TV6pocZ7BGcOY1Zv3pT0lI/9jBs7WK2d9DdLmY4vC4FBahOBzU/e6jBcnhct4vMz2LW1lGdDq4sEa1heQH6e7hp0540HhOcWsVlLWwa4776vD9vliFhgBnuI0pQ7cxTPiivLotuCFGc88+NQVZXcFc2seMxqtPB7u+j5+eQMMTuDZFTJ5DxlHr9ip92RW4rNHAkDEYQoJYXse0E1esgVY3tZQQ7HcqzC5j3LJNcHDB+ZI5oWDGdDWlbR/HRB0iuTFCVIT/VIdnwxpGyxsQh9dkFwu0Jan9CcXYBGRW+EvijT6AvXMPdtwIXGzLLlUWKk22i3Rw9Lhg9MkvnK1dwsynBA2d9NfF8Fxso9GCMnclg0rjptfF8YO5AB9P48Fig2Xl6gWSwwP4JTfdSTbw5IZ9PSC7sUj90Ar1fMn1knnYcXa9KHh11gssjGpq6WzjyC+d6IWP3Rz/un7c8S6fVTYN4BONThh/5xLOMqoSpCfnaxknySUS7kzPNQ8LQoLWl/PoM8Y4Q5I790/5YmjiqSS06V+ipULctwb5C5748zjw2ptOeUlQh42sZrYUJ+SQiSUvKMqCT5Qw2Osx+NaBqC1XXoae+KzQce2lHVeFplIwvu8P57HH/MfihT32Zti7408Epnn/hFHoYYOYrspkp40GLMC0JAkv4x11fa3mbQtLjEXYE8Y5knEVEi8hXReS3m9fHTDh3AW/Frf9ZfDP6Af4lngnnIaCPZ8CBG5hwgH/V7HeMdwh3SqxyCvgh4F8A/1BEBPiLwN9sdvk14Bfw1EU/2jwH+G/AvxERuR2TgJ3JmH73R3Diy5dVDUVPSHYtkyVN2YXTn77IpIoYlyG7V3qoqfbazKU6pGyd+XpAMPVspZNlXzXltFfSO2DUtjFEg+tUrzaE0cM17eV99q9lSKlQZUOb1G0CzNoRXQ2Z+4ZP1XjKP3+/TfqeykHnDhv60gAxHNLJbr8v4OSn1uiEOV99+Qx6N0CVgo0dpm1QaY0bRriWYekPfF+Y/a233wzxS8A/AjrN63neSSacsEv7pT2fyu/EhFv72DRGX+vTemSF6ULIq+l9BBNh9kXDKlC2hWwDxic8b2Jr25Jd2AMtuECRXQ2oW5q6pYgHNTZUXst5q6CcjQj3a/S0ppiPmX1RmCz0SGtfVifOcyWmW4oyU9QptHYs3W/2Md2EqhvhlBBvXqfLO6ANdFojZYVLQiSvyM5Z1ienWZuDlRcsYiAa+pxdlWrigWOypADF7Ll9bKBQxdugkBWRHwauOeeeFZFP3ol17wQ3MeHInDPPvwD4OfrgcmtAr1+hDbT/683HZ81jdOM5b3ium7/4hm0H+95YzB2/wTaA9DWP3HBdB/2RB51Fb4aVX371DbcffObBdTUi6+DeoHq5wZ2MsE8APyIiP9h8Rhf4Zd5BJpxj3Dne1Olwzv1j59wp59xZPEnK55xzP8E7yYRzjDvG21k4/xzvEBOOnc0Y/sDHfAdmw4lrYl+PYUOwgfDBn3iOrbyNdcK3XlwFKxBadFrjjGDHIeGupveyX3Dnc0I54zskbdA4HBHonIZW1jsFZRempwzLD2yzsTHji60ig9mOcW0DtRB2SqphxNxXfL2JLny9Rt0S0i2LCYVw6g5DUzZsaju00H9E4Z4Y8YHVdS7szbF5aY5gr+H/7Rp0r8Rux8hcSedLLcRA/ZnjhfM9heNS7e8gHBvsHsOxwe4xHIlo/YFYjlOQz3q++DoVsJ4GYnzacfapy1zYnKfbmdB/dZZwT1HNWaQUbMtCYOl9PUJVjmjoKHqKsufFdA50waqOZzMN971gTj7vCZmnKxa9mFOPQ5K1kHylRmrBxRY11Y3IjtB7ER89Ca5nE1QN8dA2HFbe2bDhAQUfXP6044GHNyjqgGuDNu5SRrgnFAsWvTLFOkHWWtQ9w9KfeGfknYh0vKvQ05r2S3uItXSdQ6YF9coMemcfO5PhvixUv7dM++GIhWcty3u77L1vHqf8F5Ts1KjKEvSHOKVwSeA5CHs+oqFKQ9WNSM5vMXnPEuGoQg8LipWMqJ9Td2LKXoQuHDasiXcKivkYp4T2S7uM3jNLdnnsScUmFbYdeaYAY1F5fV3O3l33FJ3WoIX7yg7xOc21v7zC0iuG3jPrjB9b9pXCUQjWMVlx6FLRvjT2/9PbiXT8WcAp37hgWzFVJ0IXnsquXuqCdaiy5uJPGsJXYOd9GarKMDFkG4bBgwEmFiaLiqTfovfSBD2tqDveWGUvBBeSz2lGp1bpXiqouhFVJyTcrykWWgzPhEyXhHgAcd8yWUypW4JJoMrmmCwr8tk288/tM72vQ7RXUc6FqNr5NqW9HGzTeekcTinf1WIc7W9scP6nTlG3LVWmscFJxDiqjkZVjsHDmqVnCvKFEJM0bUzHbG73Fo58xvngFyVhhDPG19Y/8agPrE5y3HCf4kMPoHNDvhDR+doGdmsHCQNYXkTKCjPfQW/0qS+ve1oIrVGdtj9/WflCmzCAyxuY0Qi9tAhlhen3QWmCkyuYxRn03pj6lQu+jqOssNs7SBJjH74Pef48kmVImoB11GuXUVmGnUyQwEcYRSs/PYpgpzn6gfsQ6xh+YBmrYeaL69RrlwlOrWLnOp6B9EvPEayexPYHfnrNj0fYPYUjP8KklSCPP46NAsT4rsuDtlSdG8puyODhkOyqYecJTe/8QWjIH69KqNpC72JN68oUGwfUWeDTKbslxUx4mDPzHp8jGhSYJKDONDYUdh4LSDc9O0AwcbT6lrLtxdiqzLcidV+devVYEWys0ZMKGp56KWt/7zI+1YJSYC1bT3uCFhOL56TX0L7inYoq9dRI4dh7xUvPjP1s85V3SMrj3cLxCLsZx6Gp7yAcG+wew7HB7jEcCafDzqRMP/kRVOkXlHUihxL0qvbMAdH3bLO90UW3DHYQIYVgZ2pkrNEThUktvXOabNPf0PfOelGcdNNRzPiISNnz542GXlHIxN6hKGcdVc+ipgqTGcQJUnonAQe25Yg3Nb3zjSiP9Tk1gHDifB2IdZhIeR3LhpnUaeHqn9PUqwVnTuxw8co84VpMNBSvTX2yRoygx77AtfuKl7y3v32cD7uncOx0fAfhSEyJrpNSfewpL2ufqEY6XhOOvd6XMo7+IxqT+Jr2aI9DrS4T+1S/OGivG4LcHkbMJ4uB11DZqil7Gqub9H3tyK5WlN0Ap6HoKIYPQjAR0g1Hnfj6fjGeTkIXfmqeeanEJNqvDWcCdO4OaWlVZQ81w8CXNajaUfYCtt/nrz0cCcm2Ix5ep1waPAzpVaHswfy3mob2z91LtA/HOPqRjgNiFafFS71riAY145MR0b4fMVc+oQkmQrFsyC5ogqkvrCm7EPeh7EHnkiUZGIKJYXgmRtVepHQ6r6kyL84dTtxNDoMuLcPTAftnoXXVF9jk80J73esuq2aUiYX2miVoGK9N5PfVuR9ZOjdeaNU2Kk21wwbCZDlk68NeMNzEnlgl2XVMF+WwIrlz0ZHP+UgNDtznj0fYPYVjp+M7CMcGu8dwJO5hdFLqjzzlayFEKLs3NHeLeA2vOUe2DsMHIRx5Bdiqg8/0Wl9nsfzlCqfxYtuzwaGnZiIhn1WHHlz7qkGVjulCQN2C0f2+2DQa+HuWGDCR73wRA7oCVUBn3RBMrb/PivcEW9teXE7nBhNr7y025GY2UGx+2KvMmtTzCHfPK6I9R9URxqccwdjLHNsQFp6r/aL7+B52b+HIe4mkCfLexw/1S5xWnvGzP8W0Y8peSP8Rr8onTZVS0jf0HwrpXaiZzmucwOyLOeHOmKqRBD4omQ7GNSbWBPsl49MpwdQSb+eYLKTsBeQ9H8ZqbRv2HgiI+45o7MNNVUsR5I5wVHt6wHZANChRtaXsRUSDAqktNtKH8h1SW5xSoIXdxzueZu+0Y/abkG1UmJbvXasyxWRZITXMvlgS9RtW0z99m8Lb7zakrFHnL4N4g0m37d3jyYRgfpbgXJ/4d3YZ/5WPEu3VRIMCvTNCzBKtL5+n9eDqobI6V7cIN7fRD6zivvwc6slHUaMpIeACTW9ti3pjE/X+xwiu9tFrl0mffuKQUVRMSnbuGvWrF6k+9RR6akm/uQFaQVESZi0YDJF2RnIpR8IQN56gAZyFMPJJzYYzZPaZXXS3i6tr7BMPEmwNcWGAa0Wo0ZTeXBu9vg1B4AXvnLutLPDxlHgEceSnREli1MOPItZSLrfR09pPM02pQLSTc+mHe4RDmDnvlYlMrGht5lTdiLrlR2Z2eYIUFTaNsIFieH+L7gXfHKf3S/pPdJn7Wh+bRn7qaZya0ZkEq4XZc/sM3pMRTnx4Kp9VdC/Wh1Nr9qrvEi0XUlRhCAY5Ng0R60sEpFG3JdBQ1RBohu+dY7qg2H26ZvkPNOmWr6E0kWL7fRHLz+aMVyJaOzXhsPTlBs8d8RKBzswp94Hv+lnA1zmo2nm95aGlSoXRfQpxUHUc5UpF65XI9y5HXhK46lmCiSJd933R4dQxnfURkwPpKhP7yIIYyDZ8X/J4RSEGilnPvaFKwWn/fZQzlvZFTb7okAqSHSG95lm9fWrGny8aNekV4w5TKuJ8FbCNhPGSYnQ/JI/sUZYB+rk2uvRtUCaG6bIj3hVfjbzn0JXjG5/9JfZ3147wCNubkPzPLwHX20izG97vfRvnTN98lzva5+0iBRbf4jHKjW/53pEwmOum5J/8CFI7posBre2afFajKygzoW4Jw0cswUioM4cuhdaGV08XCyZxiBWSa17MLZgaposhRVcakTU/yqqOHxXxwHf628ivpWzkK7Dq1BH3hbLnqFNHsq2oW/74aAi9V6rDNeIBSbNTQjD18U6n8GwFTSWVU8J4WbPzlAHtUBNNtKfILrvDa5muWOJthS7wujGA/d9HvLZeFTXtr67jshbpeQdakZ53niSs06KabWGjhHjgF8G9V0qUcV4efuwDuKpyxBv7/ovSQrSjoLa4Vkgxn3jSr/0C0/Uq7FJUuFCTL6fUqWL/hGb1D6eMziT0XnUk1wrGpxJMJKTXapyG1vo+2bmpJwqb6yCTApkWEIW+3PygIPaAv76qiU/Pky9ktC9b5r+wQXlyhnI2YlppwolFF5rWliWcWjrPXoEwQI9v7SUeCYM5rbALvcZhiLGRb2ZAQZ1o6lQzfKSm83JAnUE+H9O65qU9OmuW4ZmQuO+o0y7p5QlOCVU3opwJDiUKB4+2iYct4p2K4SMJ7fXy8L4zWtXowrH1wZRo6KhaUDzUIp8Tkl3H9pMh8a6jtS6MH13EhkKyVVCc7hD3PaObKmovQpDXmCjwdfbWki/FINB/rzBePUl6tZF1vFiw+eGEuXM1w/sC9luKaLDkIyVXb02/d0exRBG5ICLPicifisgzzbY5EfldEXmpeZxttouI/OuGuujrIvKhNz2/A5zDZjEu1NhYYyOFiTXRXolYR3YxYHLSUrUdC9+oCaeOeOAousoTscwIqnCHyg11W/tmBevTHNlGhZ5aJidiWls1wbjCRgob+T7lfEHIrvrQkzKQbtV+6rQQ7zp6r5ReGwZobeaowk+9B10skteHsvdiTKPrqUi2SqYrltlvOUzoE69B4di7P8bEsPVkQDRyBFOfBMW6m+SsXou3MsK+2zl3IznKzwO/75z7RRH5+eb1zwE/ADzc/H0Uz45za11BvGdVzbWwDSmKDQQTC7p02PmYvbM+M9x5VTF4X832EwHxwDFe9SI0xZwvrqkzRbGYNh0kgg2EnSdSgqlXsq0TP2WF+zA6kxIU3r3OZz2bznjZZ7frRCjbQj7vWW/CfSjmgibWCflCcri0UC1NuF9jw4P4ZwQiOO0/a3g2Rpam7D7eItoDq4W664uA6gzCoRcujQcOE2svxhrcehzdkVsvIheAp280mIi8AHzSOXdVRE4Af+Cce4+I/Nvm+a+/dr9bnf944Xwz3ol8mAP+r4g821AOASzfYIQNYLl5fkhd1OBGWqNDiMjPiMgzIvJMRXGHl3GMO50S/7xzbl1EloDfFZFzN77pnHMi8pZW4DdSF/XCJafnFpGs5aezMIAo9NSsEx+pGHz8FHG/ZnQ6Ipw44oEPxk5WImY++y3fDlRUyMQbX2rjW5DWt7HLc6i9MeWpOYJRgdrew6UJ9Pdgtod56RV2/45Xau++WlLMhbQvTQjWthl+5DQmEtqXc4IX1qCukXYbl7Vgp+9bm0RwtfGtRoAz1pcL1DUszTN4cp6yK8w9P2HwcMriH67jwoDJQ/OEkxo1rVF5hdoZQqCRK+Ebf2l8G5EOEfkFYB/4uxxPie8K3lYsUUQyQDnnRs3z7wX+Gdcpin6R11MX/QMR+Qze2di7nbEAyFrIe5uIuQOTBjf1+ppWwJVPxHQvOPqPQfdlf5iqoU49jWvZEboXa5LtHKkt0xMprctjpqcyJgsaG0H3Ys1kKSDpG5yGYN9QzIUEU8vuYwHtNUs+14S0LMyeKxifjBifFDqXLJ0LUx8K6/p2WZz37IJRgdOCTUKc4Ft+8VmIfCXj0vcFRENFsuUTpdmmpegJxaxfPLfXHOm1mtb6CBcF8PzbS68sA7/pKRIJgP/inPusiHwZ+A0R+WngIvDXmv1/B/hB4GVgAvzUm36CO3CHHSb11HZVFqBDhdXC3gMh1aMT6o0WOJguCUF+XTJqvOpItv2XV7VDdOFjftVcQt1S1C3fgzV4KGT2XNH8CDTB1DBqR1z7kMa0LKAIxlBlUGeOyUpEerUpG3c+gmESTZAb6sT3KKui9v1g1qL3i+tN6VEAzrF3f4ibK6lsSJ0Is+cgGhnymYCy52hf8j+6vftDdJmhyluLvcERCf6KyAh44W5fxx1igddwP74LOOOce8MQ5JGIdAAvOOeevtsXcScQkWfu5rUeV03dYzg22D2Go2Kwf3e3L+At4K5e65FwOo5x5zgqI+wYd4i7bjAR+X4ReaFJx/z8Xb6Wfy8i10TkGzdse8fSSO8E7qrBREQDv4JPybwX+Bsi8t67eEn/Afj+12w7SCM9DPx+8xpuTiP9DD6N9K7jbo+wjwAvO+decc6VwGfwyhJ3Bc65P8ITS9+IH8UrX9A8/tgN2/+j8/ginhb+xLt9jXfbYHeUirnLeFtppHcad9tg9xQa/v276lbfbYMdqEgc4EaFiaOCzYOprnm81my/K9d+tw32ZeDhRosswosS/NZdvqbX4kali9emkf5W4y1+jDtJI70TcM7d1T98KuZF4DzwT+7ytfw6cBWo8Pekn8YrM/0+8BLwe8Bcs6/gPdzzwHP4mpd3/RqPIx33GO72lHiMt4hjg91jODbYPYZjg91jODbYPYZjg91jODbYPYZjg91j+P97ZD2vY5SrVAAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "minibatch loop: 100%|██████████| 681/681 [05:42<00:00,  1.99it/s, cost=0.539]\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "epoch 2, training avg cost 0.538868\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "minibatch loop: 100%|██████████| 681/681 [05:42<00:00,  1.99it/s, cost=0.54] \n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "epoch 3, training avg cost 0.538869\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "minibatch loop: 100%|██████████| 681/681 [05:42<00:00,  1.99it/s, cost=0.54] \n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "epoch 4, training avg cost 0.538858\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "minibatch loop: 100%|██████████| 681/681 [05:42<00:00,  1.99it/s, cost=0.539]\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "epoch 5, training avg cost 0.538868\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "minibatch loop: 100%|██████████| 681/681 [05:42<00:00,  1.99it/s, cost=0.54] \n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "epoch 6, training avg cost 0.538846\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "minibatch loop: 100%|██████████| 681/681 [05:42<00:00,  1.99it/s, cost=0.54] \n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "epoch 7, training avg cost 0.538854\n"
     ]
    },
    {
     "data": {
      "image/png": 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+ptW2ZXc/DcDrpY57V7/LZDtEzb79ADzwwhYAfvyXTfz4L5tavO/bK9a26WPV2g9bbZv9949wVuJtZpRATX0DJVk/ZT4Ee1r/wnu7SR7aw3ZnXPaNlXnbO9K28EgpPPL6Ns5NwrceeJWXXXVeNv9UcpCdFDEikRL63734PgAn3fpY1vd88s6nWm27nf28XJb6AemVV0QiVyI85RIsz769C4CN2w+E4u8vb+4IxU9cqKuP3nxqbX0D+wIqylTI1HTjvnI9rFyABD0LpUXJpuVwJ0WCYdveQ90dgq80BPk9DWh3r9u6LxjDAeDnmO9uSe1JSWqRm3Kprqln7ft7eGL9Vq4Fvv/w6/zr7x9s9z1D+5awY38NAP3Kith3qK7d9n1KkpTXbubxUr+izo6lDffq2nrKvDn1mroGipPGjv019CpJ0re0iF0HauhbVkRRwjAz6uobMLOm+ddtew9RnEwwsHdqvt7MqK1v4MDhOh57fRvnB/9xWshAMN+jVH99uPcQfYGa+no2b99Pr5IkzsHBmnqG9S/l3Z0HqRzcm9KiBHura9l7qI5RA8uoa3Bs3X2I2voGJgzry97qWrbtO8zw/mUM6l3M/oOpuejNuw5SCew6cJiNu/czfmhf3t9dTe+SJPUNjv69iilJJkiYsfdQLYP6lHC4tp5t+w6zYdt+TjtqGDv317BldzWThvejtChBfUNDWt90t8xlJz22fOJs3P+ucRLdOTDDOdc0d59OXX0DHx2soX9ZMWXFSe+9DmjAgMN19Uxenvquj+hfRuXgXlQOTs3blyQTPP/ubs6cNpwtu6t5Z8dBPjtnbJtTd3EmcoJ+0U9Xs3rTRySp59qy3N7TKOZAh2IOcKCmnvJu+FV/9PVtTLL9nLG8/R+ornBiYgvnBzPp3C3ctmo9PyyBL9/3IisbchwIOfDtos2cm6zlV6vf4/pimP0Pj1BDsS+2Hwiw/wv356GZ8d94ENeFSYGXS+von/F9/GDvIT7Ye6hparSRdAG/47G3uhRnlMmpd81soZmtN7MNZra8nXafNDNnZlX+hdiShdNGAOFNg4SXjW6hfKYw/DjC2D/RtB9c//trM05TLj2JDgXdzJLAHcAiYCqwzMymttGuH3AN0DoFwkd6lSQ7biSEED2QXI7QZwEbnHMbnXM1wH3A0jbafQe4FQj06ltxsnuu4xbynKcQjWic9mxyUccKIP0pq5u9bU2Y2Uyg0jnX7uSvmV1uZmvMbM327ds7HSxAcbIHXbIWQohOkPfhrpklgH8EruuorXPuR865KudcVXl51554nXmEHpS8p9t1LrwfkaCOsDLtBnck50+GRDYabQZRwaSR9PljPz+DX9kj2Wz6hZHev/lkuTTuK2uy29V48o2lp5CLoG8BKtPWR3vbGukHHA08bmZvAycCK4K6MNpdUy5CFDJxuFdC5E8u6vgsMNHMxptZCXABsKLxRefcHufcUOfcOOfcOOBp4Czn3JogAm6ccgkz+yQcPxBGxQvnwshyCcdHFO27gI4z/S5E6G+Wi35swqJDQXfO1QFXAauAdcD9zrm1ZnazmZ0VdICZlOgIXQgh2iSnG4uccyuBlRnbbszSdl7+YWWnuEiCLoIj6vO0Ohbu2UROHTtbZlQIIXoKkRP07pDzaB+zxZMg52U156s7RaNK9AQ9o6hPWGl+QRFeOmH7foOwG1RKXTZ/hU963/hDIEUEzJ84/RrbFlrKQPSJnqB3dwBCFCA6qxAQQUFvrJYY3gAOK20xnGNNR/CnwGH5iKL9oI41C1vQCzm2eBE5Qa/Xk7+FEKJNIifo3ZXkkuvx83GVAwOOJHge++o8TpowlJ9eckLTNr/z/++7/EROmVTOHZ+e2bTttCnDsra/ZO44X/1nI1pz8q0JI/4BvYoZ1q+U//hsFT+5uIr+ZZF7rEJsiZygF+oB+os3nsHqb5zG7744l3FDUk97fuFbZ2Rt/4V5R4YVWgvK+7V+DNMVpxzBkD7NT1+oHNSL//zcbOZPHsZL3/4YN31iKm/csoijK1JPhG/838jdn63i3s/NBlIXrZccM7KVjzOmDqdiYPOjgqeN6s89l85iybEj+fP187n1k8fw44ubf0A+OXN0i/dfvWAiU0b068InjhZfWjCBeZPLeerrC4D2f+RyZe6EITxw5Rw2/cNirl84mW8uOarNdiMH5PagkKe+voDVN5zO6VOHs2DKcJ5cvqDVvpk/uWu1mkR+RO6ntSFD0dOvyPtJ+pHOuPK+UFfDHafP5J2PDnD29ApG9C/j3x/fQH0DXHjiGAb2bhbEx782v2n5rs/MpLxfGTMqB7LjwGHe++gg6z/YzwUnVPKV0yfxwY6dcFcgH6HNz3PuzAoGvVTChVPHcMGihRQlEiQTxvULp1Bbn3pEWlHa0fiAXsVcPHc8AL+9ci4NDkq8m7saGhw19Q1Njwt7+3tL4GYYN6QPoycPI7GvnvWfX4hhlBQlqG9wHK6rB6B3SfPQqxzcm/MHjwFg/XcXkjSjKJng++cdx+G6+qb3P/TlU/jKN1L3tzUXfPJ//6db9Lc4V9t2L5w9hl8+8y4AnzlxLMP7p4T17e8tAWDB9x9n4/YD3PHpmfz9ynXMnTCERUePZOueQ/z8d6lCqCdPHAqb4IpTj+Ct0smcO7OCe595l007DnDbp45t6u8r502gvsFxsKaeM6eNSD2i71AtyYQxYVhfHl77IcP/UMrIwUPgXfjO2dP49rEfo7QowZ6DtZhZi30H0K+smIe+fErrD3zgCLg9/33VnOVSoEdzBUTkBT0MRg0og/oko45teeR51YKJHb534dHN7xnWr4xh/co4fuxgAEoSxpjBvf0NtgPM+ytKGEVpD8JOJoxkov2HhxRlTLskEkZZlvcUJQys5cO2k4nWYpBJevu21uPA9MqBUDaQt/92SdO2W845Jmv7R6+b17S8JGMMfnrcKXAnjPLOfhZOGwmVEwC47mOT27SXTBhXn9b22P3EcaPg0UTTk5V7FyehLPUIvmH947cv4kbkplyan7Mbt0fQhZOp4LDgH4NujT8bwRHl4lyB9I3f+9RHezquDo/oCXqhTqJHBPWeEPElgoIerr9xQ/uE6zBg9HsoRHyJnKC7kBWptLG6o5SwIGi8ABsU0b8FRuO0JxM9Qc9Yz/ULOGl43y75+8SxozrhpQtkZu0EXGPFNdoP6geqhV3/fUz29mPUH0HnX98EsB/92odOj6ALm8gJ+ulHDefC2WNybv+1Mydz92erePgrp+bUfnrGjUG9S+J1Zf+Yimjf+NRPN7FkIfrnFl3l0ety+273BCIn6CVFCW455xj++fzprV675Zyj+cGyGU3rf75+Pl+cP4Ezpg4H4PXvLGTDLYv45edmM7RvCfMnl/PHa0/htCnDmDAsdeR3/xX/i59ecgJTvCPB8v653WyRLyeMH5JTZsXcCUPy8jNyQC+C//IHl0nzieNGNfvwkcwbYzo6Fky/SaojRqXdsNOvrDiYvinoLJf2bf34os49fvjkiUObll+56WMcUd6XGz8+tUWb31w5hxljUgcvVy+Y0Cn7USayhztnz6iA38E1p03kmvlLWrx2VtOXviWN869zJwxlzTeb7+JMv0MRYP7kYcwffDzc4XPQ7TBlRD+ef6fltsXHjODaMyZx+j8+0bTtl587kUO19dz9xEYuOWk8G7fv56x/e7Lp9XNmVPDy5t28t6uamroG3vjuIv7jLxt5/cn1UBvWpwmO9koQrLz6ZBb/4M9N6y/d+DGOu/lhIHWTzrjlD2Z974NXn8w3fvMKR33YjwH7imFfy9f/6fzj+NXq91i96SMgJRiL/+XP7DxQw2Nfncf8//N4m3bPmVHBbZ86ls/fs4bhO8oYOHwg1OzO8dPGn78uX9CUQ5/Jzy+dxXX3v0iy3sCl7nv409fmMXZIH3bsP0xRwlI/kMClJ43n0pPGt3j/A1fODTz+QiOygh43Rg/qzeFR/Rlb05u3r2n5A9V4x2AjZcVJvuTdGHJMxQCuOW0i559QyepNH/HxY0e2ugHoynkToHIG/CLYz9Ad/GDZDG4/aiElyQRmxsRhfXlz236+sXgKA3oXZ33f4mNGUN63lJ8/9Q43LD6KZMK49VPHwoODYW3zEWXvkiTVNXDG1BHU1rkmQe9TWsQVpx7B3698nSF9S7K54cQjBlOcTPCzS2bBD0uhhz8TN2Hw2s0LmfKthzi6on9WMQc4Ymif1IHXLQmoTZ2TjR2Syjob2rd1CQsRwSmX7iPYCzIGTCjvS7KTp7pmxlfOmMSogb04e0ZFKzGPK2dOG9G0XFqUbHrwyYqrTuKFb53B5ae0rpVz7+dnc8Pio3j7e0v49wuPp7itvvIu5J02JTVN94NlMzh1Ujm9i5P0KU0d/0yvHEjf0iIuP+VI3v7eEvqXFTcVD1t0dCqufl7bXh3cGes7BZ6Ndf3CKZQVJ/npJSdwz6Wzm7b/ywWpKdRzZ1R0V2ixQEfoIpIsmzUG3my9vVdJkl5pF7LXfPN0DtWm6sfMOXIoc45snn+9aM44Hl2/jaXTW0/RzT5iMLwFc48cytyjxgIpsb556TTOq6ps1X75olQtnOvOmMydnzme6pp67l39Lh9vo1BZT+XN7y6CotTZzPzJLYuOLZ1ewdLpKTEvK0ly7zPv0rdU8tRZot9jYaTfBXqrfGb8wT5aIVQ/gbjISFjsYP+3d2peObh3izopzaTt7zT7iYTx2f81rk1bpUVJvnt2cz2WXiVJLsuY023ZNz51TiDj35Fr/3ZsJ/1T52brf581jS+ceiSDGiuANsZQ4GcfhUDPOD8XIvYUbtpiv04eaRcnE1SGXLQuLkRc0MMYxCF9USyEollh+QmhOFfwuyUgB0H1TQGnLfYry37RWPhLxAVdCCFEIxJ0IYSICRL0XNEFmR5C1Pdz1OMX+RADQQ8jKyS84lzhFM0Ky0+QhaMa90kAPlrMH/toP5C+CaqPfejfxs9r+WbMuIz/IhsxEHQhRCFnuYjwiLagh5UVEgohZIaE5iesTJoo2g+obwo4y0U/NuGRk6Cb2UIzW29mG8xseRuvX2tmr5nZy2b2iJmN9T9UIYQQ7dGhoJtZklTdwUXAVGCZmU3NaPYCUOWcOxb4b+A2vwMVQgjRPrkcoc8CNjjnNjrnaoD7gKXpDZxzjznnDnqrTwOj/Q2zENAFmR5B1LOZoh6/yItcBL0CeC9tfbO3LRuXAb9v6wUzu9zM1pjZmu3bt+cepRBCiA7x9aKomX0GqAJub+t159yPnHNVzrmq8vJyf5yqOFfh+gmscBT4UzwqG20X58qfIItz+TlG/S3O1RxaF23prCNncqmaswVIrxc62tvWAjM7HbgBONU5d9if8DpCtVwK0k8sso9Uy8VHYz7aEu2RyxH6s8BEMxtvZiXABcCK9AZmNgP4IXCWc26b/2EKIYToiA4F3TlXB1wFrALWAfc759aa2c1mdpbX7HagL/BfZvaima3IYk4IIURA5FSo2Dm3EliZse3GtOXTfY5LCCFEJ4n2naJhogszPYSo7+eoxy/yIQaCHlZWSFBuwiqa1YHfUJz6YTKsbJ0A7LusK34Z9cmkT0XEfBvbQWdOxYcYCHoY6Cp94RHgPgmtfo+f+B2zj/Yi2Z/RJNqCHov0uCZHqDhXZ1xE1b6Kc4ngiLagCyGEaEKCLoQQMUGCnjO6GNMjiPpFt6jHL/Ii+oIe1iPbAiNGtVxCydgJKSsoEPtB1nLxE7/i9GnMOWW55Er0BT0MdJW+AAlyn0RxfyvLRURe0FWcqyD9BFWAqpWPQB0EZFbFuURwRFzQhRBCNCJBF0KImCBBF0KImCBBzxVdXe8hRH0/Rz1+kQ8xEPS4FecKy09EC2e1euRalIpzhfBIPl9Mpj2Czo/iXI0XWP0ozqUfrHaJtqCHVsslLjVWwvIT8VouQWcCqZaLCIhoC7oQQogmJOhCCBETJOhCCBETJOhCCBEToi/ooRXn6q5iXUHZjWrhrIB9BJoNFEJxLl/sqjhXVIm+oIeBigsVICrOFSwqzhVFIi7oKs7VeT+oOFduDgIyq+JcIjgiLuhCCCEakaALIURMkKALIURMiIGgh5QVElY2TWh+QvARxmPufPcRYBZFi2Ktd48AAAhYSURBVNj98hNAf/gVp29jW7VcciUGgi56JrrQ1pIC7g9luYRGtAVdxbkK1I+Kc7VjXMW5us1G/Im2oAshhGhCgi6EEDEhJ0E3s4Vmtt7MNpjZ8jZeLzWzX3uvP2Nm4/wOVAghRPt0KOhmlgTuABYBU4FlZjY1o9llwC7n3ATgn4Bb/Q5UCCFE+xTl0GYWsME5txHAzO4DlgKvpbVZCtzkLf838G9mZs6FUEnn+XvgjVX+262tbrm+bR3cMdt/Pw11Ldf3bQ3Gz+H9LdfX/Q9sWeOvj8zd/dEm/z9L9S5vwbtI9sh34K//6p/9vVuhtG/z+o/PgEQuX5Mc+GgjDJ2YWt7yvD990zROvf747ZVQ0ic/m9UfNdv7022w+u6u2amv8ULzbN29ABLJzttxDWCJ1Pi6c248smZOvR6O/qTvZnMZqRXAe2nrm4HMkdjUxjlXZ2Z7gCHAjvRGZnY5cDnAmDFjuhhyGqd8FT54JX872Rg7B0bPAgyKy4LzM3I6TDgNhh0FNfsJLNe2bEHKx9yr4Z0ng/ExfBpMWQwVM1JfxCDoNxJGzYBZl8P+D/21XT4ZxsyBCafD0Z+Chlp/bc/4Wzi8D3oP9s/u2LlQdQkc3JGynS/lU2D2FTBgNOzdkp+tiiqYvgxe+GXX+3LYVJi0EN5c1foAKKqUDQzErHV0EG1mnwIWOuc+563/LTDbOXdVWptXvTabvfW3vDY72rIJUFVV5das8fkIUQghYo6ZPeecq2rrtVwuim4BKtPWR3vb2mxjZkXAAGBn50MVQgjRVXIR9GeBiWY23sxKgAuAFRltVgAXecufAh4NZf5cCCFEEx3OoXtz4lcBq4Ak8BPn3FozuxlY45xbAfwY+IWZbQA+IiX6QgghQiSny/fOuZXAyoxtN6YtHwL+xt/QhBBCdAbdKSqEEDFBgi6EEDFBgi6EEDFBgi6EEDGhwxuLAnNsth14p4tvH0rGXagFguLqHIUYVyHGBIqrs8Q5rrHOufK2Xug2Qc8HM1uT7U6p7kRxdY5CjKsQYwLF1Vl6alyachFCiJggQRdCiJgQVUH/UXcHkAXF1TkKMa5CjAkUV2fpkXFFcg5dCCFEa6J6hC6EECIDCboQQsSEyAl6Rw+s9tlXpZk9ZmavmdlaM7vG236TmW0xsxe9v8Vp7/m6F9t6MzszqLjN7G0ze8Xzv8bbNtjM/mBmb3r/B3nbzcx+4Pl+2cxmptm5yGv/ppldlM1fjjFNTuuTF81sr5l9uTv6y8x+YmbbvIevNG7zrX/M7Hiv/zd4783puWhZ4rrdzF73fD9gZgO97ePMrDqt3+7qyH+2z9iFmHzbZ5Yqvf2Mt/3XlirD3dW++nVaTG+b2Yth9pX3vmy60O3jC+dcZP5Ile99CzgCKAFeAqYG6G8kMNNb7ge8QepB2TcBX22j/VQvplJgvBdrMoi4gbeBoRnbbgOWe8vLgVu95cXA70k9KPJE4Blv+2Bgo/d/kLc8yMd99QEwtjv6CzgFmAm8GkT/AKu9tua9d1EecX0MKPKWb02La1x6uww7bfrP9hm7EJNv+wy4H7jAW74L+EJX+yrj9e8DN4bZV17bbLrQ7eMrakfoTQ+sds7VAI0PrA4E59xW59zz3vI+YB2p56dmYylwn3PusHNuE7DBizmsuJcCP/eWfw6cnbb9HpfiaWCgmY0EzgT+4Jz7yDm3C/gDsNCnWE4D3nLOtXc3cGD95Zx7glRt/kx/efeP91p/59zTLvXtuyfNVqfjcs497JxrfFjm06SeCpaVDvxn+4ydiqkdOrXPvCPLBaQeHp9zTB3F5dk9D/hVezb87isvrmy60O3jK2qC3tYDq9sTWN8ws3HADOAZb9NV3unTT9JO1bLFF0TcDnjYzJ6z1MO3AYY757Z6yx8Aw7shrkYuoOWXrbv7C/zrnwpv2e/4AC4ldUTWyHgze8HM/mRmJ6fFm81/ts/YFfzYZ0OA3Wk/WH711cnAh865N9O2hd5XGbrQ7eMraoLeLZhZX+D/Al92zu0F7gSOBKYDW0md+oXNSc65mcAi4Itmdkr6i94ve7fkpHpzpGcB/+VtKoT+akF39k82zOwGoA74pbdpKzDGOTcDuBa418z652ovz89YcPssg2W0PGAIva/a0IW87PlB1AQ9lwdW+4qZFZPaab90zv0GwDn3oXOu3jnXANxN6nSzvfh8j9s5t8X7vw14wIvhQ+90rfFUc1vYcXksAp53zn3oxdjt/eXhV/9soeW0SN7xmdnFwMeBCz0xwJvW2OktP0dqjnpSB/6zfcZO4eM+20lqiqEoY3uX8WydC/w6Ld5Q+6otXWjHXnjjK5eJ9kL5I/XIvI2kLsY0XniZFqA/IzV/9c8Z20emLX+F1JwiwDRaXjDaSOpika9xA32AfmnLfyU19307LS/K3OYtL6HlRZnVrvmizCZSF2QGecuDfei3+4BLuru/yLhQ5mf/0Pqi1eI84loIvAaUZ7QrB5Le8hGkvtTt+s/2GbsQk2/7jNSZWvpF0Su72ldp/fWnbuyrbLrQ7eMrECEM8o/UFeM3SP0C3xCwr5NInTa9DLzo/S0GfgG84m1fkTH4b/BiW0/alWk/4/YG7Eve39pGe6TmKx8B3gT+mDY4DLjD8/0KUJVm61JSF7Y2kCbCecTWh9RR2YC0baH3F6nT8a1ALak5yMv87B+gCnjVe8+/4d113cW4NpCaS20cY3d5bT/p7d8XgeeBT3TkP9tn7EJMvu0zb7yu9j7nfwGlXe0rb/vPgL/LaBtKX3WgC90+vnTrvxBCxISozaELIYTIggRdCCFiggRdCCFiggRdCCFiggRdCCFiggRdCCFiggRdCCFiwv8HiYCUqofY0rkAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "minibatch loop: 100%|██████████| 681/681 [05:42<00:00,  1.99it/s, cost=0.539]\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "epoch 8, training avg cost 0.538862\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "minibatch loop: 100%|██████████| 681/681 [05:42<00:00,  1.99it/s, cost=0.539]\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "epoch 9, training avg cost 0.538872\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "minibatch loop: 100%|██████████| 681/681 [05:42<00:00,  1.99it/s, cost=0.54] \n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "epoch 10, training avg cost 0.538868\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "from tqdm import tqdm\n",
    "import time\n",
    "\n",
    "LOSS = []\n",
    "maxlen = 50000\n",
    "\n",
    "for count in range(epoch):\n",
    "    pbar = tqdm(\n",
    "        range(0, len(X), batch_size), desc = 'minibatch loop')\n",
    "    train_cost = []\n",
    "    for i in pbar:\n",
    "        batch_x = X[i : min(i + batch_size, len(X))]\n",
    "        batch_x = tf.keras.preprocessing.sequence.pad_sequences(\n",
    "            batch_x, dtype = 'float32', padding = 'post'\n",
    "        )[:, :maxlen]\n",
    "        while True:\n",
    "            try:\n",
    "                _, cost = sess.run(\n",
    "                    [model.optimizer, model.cost],\n",
    "                    feed_dict = {model.X: batch_x},\n",
    "                )\n",
    "                break\n",
    "            except Exception as e:\n",
    "                print(e)\n",
    "                time.sleep(1)\n",
    "        train_cost.append(cost)\n",
    "        pbar.set_postfix(cost = cost)\n",
    "    train_cost = np.mean(train_cost)\n",
    "    LOSS.append(train_cost)\n",
    "    print('epoch %d, training avg cost %f'%(count + 1, train_cost))\n",
    "    \n",
    "    p, l, t = sess.run([tf.nn.sigmoid(model.predictions), model.labels, model.targets], feed_dict = {model.X: X[:1]})\n",
    "    plt.plot(p)\n",
    "    plt.plot(l)\n",
    "    plt.show()\n",
    "    \n",
    "    plt.imshow(t[0].T)\n",
    "    plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "batch_x = X[-2:]\n",
    "batch_x = tf.keras.preprocessing.sequence.pad_sequences(\n",
    "    batch_x, dtype = 'float32', padding = 'post'\n",
    ")\n",
    "logits, targets, neg = sess.run([model.logits, model.targets, model.negatives], feed_dict = {model.X: batch_x})\n",
    "logits.shape, targets.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "scrolled": true
   },
   "outputs": [],
   "source": [
    "plt.figure(figsize = (15, 5))\n",
    "\n",
    "plt.subplot(1,3,1)\n",
    "plt.imshow(targets[0].T)\n",
    "plt.subplot(1,3,2)\n",
    "plt.imshow(logits[0].T)\n",
    "plt.subplot(1,3,3)\n",
    "plt.plot(X[-2])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "p, l = sess.run([tf.nn.sigmoid(model.predictions), model.labels], feed_dict = {model.X: X[:1]})\n",
    "plt.plot(p)\n",
    "plt.plot(l)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "saver = tf.train.Saver(tf.trainable_variables())\n",
    "saver.save(sess, 'wav2vec/model.ckpt')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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